Preprint
Hang Li*, Kaiqi Yang*, Xianxuan Long, Fedor Filippov, Yucheng Chu, Yasemin Copur-Gencturk, Peng He, Cory Miller, Namsoo Shin, Joseph Krajcik, Hui Liu, Jiliang Tang
How Uncertain Is the Grade? A Benchmark of Uncertainty Metrics for LLM-Based Automatic Assessment
Preprint, 2026
Xinnan Dai, Kai Guo, Chung-Hsiang Lo, Shenglai Zeng, Jiayuan Ding, Dongsheng Luo, Subhabrata Mukherjee, Jiliang Tang
GraphGhost: Tracing Structures Behind Large Language Models
Preprint, 2025
Pengfei He, Zitao Li, Yue Xing, Yaling Li, Jiliang Tang, Bolin Ding
Make LLMs Better Zero-Shot Reasoners: Structure-Oriented Autonomous Reasoning
Preprint, 2024
Xinnan Dai, Qihao Wen, Yifei Shen, Hongzhi Wen, Dongsheng Li, Jiliang Tang, Caihua Shan
Revisiting the Graph Reasoning Ability of Large Language Models: Case Studies in Translation, Connectivity and Shortest Path
Preprint, 2024
Jie Ren, Yingqian Cui, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu
EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations
Preprint, 2024
Guangliang Liu*, Haitao Mao*, Bochuan Cao, Zhiyu Xue, Kristen Johnson, Jiliang Tang, Rongrong Wang
On the Intrinsic Self-Correction Capability of LLMs: Uncertainty and Latent Concept
Preprint, 2024
Jie Ren, Han Xu, Pengfei He, Yingqian Cui, Shenglai Zeng, Jiankun Zhang, Hongzhi Wen, Jiayuan Ding, Hui Liu, Yi Chang, Jiliang Tang
Copyright Protection in Generative AI: A Technical Perspective
Preprint, 2024
Han Xu, Menghai Pan, Zhimeng Jiang, Huiyuan Chen, Xiaoting Li, Mahashweta Das, Hao Yang
Towards Generating Adversarial Examples on Mixed-type Data
Preprint, 2022
Wenqi Fan, Xiangyu Zhao, Xiao Chen, Jingran Su, Jingtong Gao, Lin Wang, Qidong Liu, Yiqi Wang, Han Xu, Lei Chen, Qing Li
A Comprehensive Survey on Trustworthy Recommender Systems
Preprint, 2022
Yaxin Li, Xiaorui Liu, Han Xu, Wentao Wang, Jiliang Tang
Enhancing Adversarial Training with Feature Separability
Preprint, 2022
Publications in 2027
Haoyu Han, Juanhui Li, Wei Huang, Xianfeng Tang, Hanqing Lu, Chen Luo, Hui Liu, Jiliang Tang
Node-wise Filtering in Graph Neural Networks: A Mixture of Experts Approach
In Proceedings of the 20th ACM International Conference on Web Search and Data Mining (WSDM), 2027
Hanbing Wang, Bingheng Li, Jingzhe Liu, Daochen Zha, Chun How Tan, Xin Liu, Jiliang Tang, Huiji Gao, Stephanie Moyerman, Sanjeev Katariya
Bridging Collaborative-Semantic and Training-Inference Gaps in Generative Recommendation
In Proceedings of the 20th ACM International Conference on Web Search and Data Mining (WSDM), 2027
Publications in 2026
Yuping Lin, Pengfei He, Yue Xing, Yingqian Cui, Jiayuan Ding, Subhabrata Mukherjee, Hui Liu, Zhen Xiang
Crafting Reversible SFT Behaviors in Large Language Models
★ NeurIPS Financial Assistance Award · In Proceedings of the 40th Conference on Neural Information Processing Systems (NeurIPS), 2026
Shenglai Zeng, Tianqi Zheng, Chuan Tian, Dante Everaert, Yau-Shian Wang, Yupin Huang, Michael J. Morais, Rohit Patki, Jinjin Tian, Xinnan Dai, Kai Guo, Monica Xiao Cheng, Hui Liu
Attn-GS: Attention-Guided Context Compression for Efficient Personalized LLMs
★ Oral | SAC Highlight · In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026
Zidi Xiong*, Yuping Lin*, Wenya Xie*, Pengfei He, Zirui Liu, Jiliang Tang, Himabindu Lakkaraju, Zhen Xiang
How Memory Management Impacts LLM Agents: An Empirical Study of Experience-Following Behavior
★ Oral · In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026
Yu Song, Zhigang Hua, Yan Xie, Bingheng Li, Jingzhe Liu, Bo Long, Jiliang Tang, Hui Liu
Learning the Latent Structure: A Feature-Centric Approach to Graph Data Augmentation
★ Oral · In Proceedings of the 40th AAAI Conference on Artificial Intelligence (AAAI), 2026
Shenglai Zeng, Qirui Wang, Kai Guo, Xinnan Dai, Xianxuan Long, Hui Liu
Magnifying What Matters: Attention-Guided Adaptive Rendering for Visual Text Comprehension
In Proceedings of the 40th Conference on Neural Information Processing Systems (NeurIPS), 2026
Haoyu Han, Li Ma, Hanbing Wang, Bingheng Li, Daochen Zha, Chun How Tan, Huiji Gao, Xin Liu, Stephanie Moyerman, Sanjeev Katariya, Hui Liu, Jiliang Tang
An Embarrassingly Simple Graph Heuristic Reveals Shortcut-Solvable Benchmarks for Sequential Recommendation
In Proceedings of the 40th Conference on Neural Information Processing Systems (NeurIPS), 2026
Pengfei He, Zhenwei Dai, Xianfeng Tang, Yue Xing, Hui Liu, Jingying Zeng, Qiankun Peng, Shrivats Agrawal, Samarth Varshney, Suhang Wang, Jiliang Tang, Qi He
To trust or not to trust: Attention-based Trust Management for LLM Multi-Agent Systems
In Proceedings of the 40th Conference on Neural Information Processing Systems (NeurIPS), 2026
Bingheng Li, Shikun Liu, Yu Song, Jay Revolinsky, Haoyu Han, Jiayuan Ding, Hua Liu, Jiliang Tang
Understanding Graph Self-Supervised Pre-training under Distribution Shifts: A Scaling Law Perspective
In Proceedings of the 40th Conference on Neural Information Processing Systems (NeurIPS), 2026
Jingzhe Liu, Zhigang Hua, Yan Xie, Bingheng Li, Harry Shomer, Yu Song, Kaveh Hassani, Jiliang Tang
Higher-order Structure Boosts Link Prediction on Temporal Graphs
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2026
Haoyu Han, Yuming Liu, Lei Huang, Lizhu Zhang, Jiliang Tang, Xiangjun Fan
ConnectionMind: Leveraging Social Networks and Large Language Models for Personalized Recommendation at Meta
In Proceedings of the 35th ACM International on Conference on Information and Knowledge Management (CIKM), 2026
Hang Li*, Fedor Filippov*, Yuping Lin, Pengfei He, Kaiqi Yang, Yucheng Chu, Yingqian Cui, Hui Liu, Jiliang Tang
Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems
In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026
Kai Guo, Xinnan Dai, Shenglai Zeng, Harry Shomer, Haoyu Han, Yu Wang, Hui Liu
Beyond Static Retrieval: Opportunities and Pitfalls of Iterative Retrieval in GraphRAG
In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026
Hang Li, Kaiqi Yang, Yucheng Chu, Hui Liu, Jiliang Tang
Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026
Jingzhe Liu, Hanbing Wang, Liam Collins, Jiliang Tang, Tong Zhao, Neil Shah, Mingxuan Ju
Beyond Fixed Depths and Widths: Optimizing Textual Decoding Tries in LLM-based Generative Recommendation
In Proceedings of the 20th ACM Conference on Recommender Systems (RecSys), 2026
Kai Guo, Xinnan Dai, Zhibo Zhang, Nuohan Lin, Shenglai Zeng, Jie Ren, Haoyu Han, Jiliang Tang
Why Retrieval-Augmented Generation Fails: A Graph Perspective
In Proceedings of The 2026 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2026
Fali Wang*, Chenglin Weng*, Xianren Zhang, Siyuan Hong, Hui Liu, Suhang Wang
GraphSkill: Documentation-Guided Hierarchical Retrieval-Augmented Coding for Complex Graph Reasoning
In Proceedings of The 2026 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2026
Jingzhe Liu, Liam Collins, Jiliang Tang, Tong Zhao, Neil Shah, Clark Mingxuan Ju
Understanding Generative Recommendation with Semantic IDs from a Model-scaling View
In Proceedings of The 2026 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2026
Haoyu Han, Li Ma, Yu Wang, Harry Shomer, Kai Guo, Yongjia Lei, Zhisheng Qi, Zhigang Hua, Bo Long, Hui Liu, Charu C. Aggarwal, Jiliang Tang
RAG vs. GraphRAG: A Systematic Evaluation and Key Insights
In Proceedings of The 2026 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2026
Nickolina Yankova, Jinhyo Cho, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Jiliang Tang
Designing Professional Development in Mathematics Teacher Education with AI as a Facilitator: A Roadmap Grounded in High-Quality Professional Development Features
In Journal of Mathematics Teacher Education, 2026
Xinnan Dai, Kai Yang, Cheng Luo, Shenglai Zeng, Kai Guo, Jiliang Tang
When Do Hallucinations Arise? A Graph Perspective on the Evolution of Path Reuse and Path Compression
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026
Jiankun Zhang*, Shenglai Zeng*, Kai Guo, Xinnan Dai, Hui Liu, Jiliang Tang, Yi Chang
Fix Before Search: Benchmarking Agentic Query Visual Pre-processing in Multimodal Retrieval-augmented Generation
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026
Bohan Wang, Zewen Liu, Lu Lin, Hui Liu, Li Xiong, Ming Jin, Wei Jin
Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026
Pengfei He, Ash Fox, Lesly Miculicich, Stefan Friedli, Daniel Fabian, Burak Gokturk, Jiliang Tang, Chen-Yu Lee, Tomas Pfister, Long T. Le
Co-RedTeam: Orchestrated Security Discovery and Exploitation with LLM Agents
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026
Quang Truong, Yu Song, Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
Plain Transformers are Surprisingly Powerful Link Predictors
In Proceedings of the 43rd International Conference on Machine Learning (ICML), 2026
Yuping Lin, Zitao Li, Yue Xing, Pengfei He, Yingqian Cui, Yaliang Li, Bolin Ding, Jingren Zhou, Jiliang Tang
Retrieval Heads are Dynamic
In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026
Yuxiang Wang, Xinnan Dai, Wenqi Fan, Yao Ma
Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation
In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026
Yingqian Cui, Zhenwei Dai, Pengfei He, Bing He, Hui Liu, Xianfeng Tang, Jingying Zeng, Suhang Wang, Yue Xing, Jiliang Tang, Benoit Dumoulin
A Reward-Guided Dual-Phase Framework for Adaptive Inference-Time Reasoning
In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026
Yucheng Chu, Haoyu Han, Shen Dong, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Joseph Krajcik, Namsoo Shin, Hui Liu
From Flat to Structural: Enhancing Automated Short Answer Grading with GraphRAG
In Proceedings of the 19th International Conference on Educational Data Mining (EDM), 2026
Yucheng Chu, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Kevin Haudek, Joseph Krajcik, Jiliang Tang
Optimizing In-Context Demonstrations for LLM-based Automated Grading
In Proceedings of the 27th International Conference on Artificial Intelligence in Education (AIED), 2026
Yucheng Chu, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Joseph Krajcik, Namsoo Shin, Jiliang Tang
Confusion-Aware Rubric Optimization for LLM-based Automated Grading
In Proceedings of the 19th International Conference on Educational Data Mining (EDM), 2026
Kaiqi Yang*, Hang Li*, Yucheng Chu, Ahreum Han, Yasemin Copur-Gencturk, Hui Liu
A LLM-Driven Multi-Agent Systems for Professional Development of Mathematics Teachers
In Proceedings of the 27th International Conference on Artificial Intelligence in Education (AIED), 2026
Namsoo Shin, Xunlei Qian, Hang Li, Yucheng Chu, Cory Miller, Joseph Krajcik, Jiliang Tang, Yue Xing
An AI-Enhanced Assessment Framework for Analyzing Middle School Science Students' Written Responses
Journal of Educational Measurement, 2026
Tai-Quan Peng, Kaiqi Yang, Sanguk Lee, Hang Li, Yucheng Chu, Yuping Lin, Hui Liu
Beyond Partisan Leaning: A Comparative Analysis of Political Bias in Large Language Models
In Journal of Information Technology & Politics, 2026
Zhikai Chen, Han Xie, Jian Zhang, Jiliang Tang, Xiang song, Huzefa Rangwala
Relatron: Automating Relational Machine Learning over Relational Databases
In Proceedings of International Conference on Learning Representations (ICLR), 2026
Pengfei He, Zhenwei Dai, Bing He, Hui Liu, Xianfeng Tang, Hanqing Lu, Juanhui Li, Jiayuan Ding, Subhabrata Mukherjee, Suhang Wang, Yue Xing, Jiliang Tang, Benoit Dumoulin
TRAJECT-Bench:A Trajectory-Aware Benchmark for Evaluating Agentic Tool Use
In Proceedings of International Conference on Learning Representations (ICLR), 2026
Haoyu Han, Kai Guo, Harry Shomer, Yu Wang, Yucheng Chu, Hang Li, Li Ma, Jiliang Tang
Reasoning by Exploration: A Unified Approach to Retrieval and Generation over Graphs
In Proceedings of the 33rd ACM Web Conference (WWW), 2026
Shen Dong*, Mingxuan Zhang*, Pengfei He*, Li Ma, Bhavani Thuraisingham, Hui Liu, Yue Xing
PEAR: Planner-Executor Agent Robustness Benchmark
In Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2026
Publications in 2025
Xinnan Dai, Chung-Hsiang Lo, Kai Guo, Shenglai Zeng, Dongsheng Luo, Jiliang Tang
Uncovering Graph Reasoning in Decoder-only Transformers with Circuit Tracing
★ Spotlight · In the Workshop on Efficient Reasoning, the 39th Conference on Neural Information Processing Systems (NeurIPS), 2025
Jie Ren, Kangrui Chen, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu
Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models
★ Oral · In Proceedings of the 34th Web Conference (TheWebConf), 2025
Xinnan Dai*, Kai Yang*, Jay Revolinsky, Kai Guo, Aoran Wang, Bohang Zhang, Jiliang Tang
From Sequence to Structure: Uncovering Substructure Reasoning in Transformers
In Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS), 2025
Jie Ren, Zhenwei Dai, Xianfeng Tang, Yue Xing, Shenglai Zeng, Hui Liu, Jingying Zeng, Qiankun Peng, Samarth Varshney, Suhang Wang, Qi He, Charu C. Aggarwal, Hui Liu
Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy
In Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS), 2025
Wenzhuo Tang, Haitao Mao, Danial Dervovic, Ivan Brugere, Saumitra Mishra, Yuying Xie, Jiliang Tang
Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models
In Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS), 2025
Shen Dong*, Shaochen Xu*, Pengfei He*, Yige Li, Jiliang Tang, Tianming Liu, Hui Liu, Zhen Xiang
Memory Injection Attacks on LLM Agents via Query-Only Interaction
In Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS), 2025
Quang Truong, Zhikai Chen, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
A Pre-training Framework for Relational Data with Information-theoretic Principles
In Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS), 2025
Yucheng Chu, Hang Li, Kaiqi Yang, Harry Shomer, Hui Liu, Yasemin Copur-Gencturk, Jiliang Tang
A LLM-Powered Automatic Grading Framework with Human-Level Guidelines Optimization
In Proceedings of the 18th International Conference on Educational Data Mining (EDM), 2025
Kaiqi Yang, Hang Li, Yucheng Chu, Zitao Liu, Mi Tian, Hui Liu
Iterative LLM-Based Generation and Refinement of Distracting Conditions in Math Word Problems
In Proceedings of the International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2025
Yucheng Chu*, Hang Li*, Kaiqi Yang, Yasemin Copur-Gencturk, Jiliang Tang
LLM-based Automated Grading with Human-in-the-Loop
In Proceedings of the International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2025
Yang Nan, Pengfei He, Ravi Tandon, Han Xu
Can Multiple Responses from an LLM Reveal the Sources of Its Uncertainty?
In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025
Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data
In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025
Jiankun Zhang, Shenglai Zeng, Jie Ren, Tianqi Zheng, Hui Liu, Xianfeng Tang, Hui Liu, Yi Chang
Beyond Text: Unveiling Privacy Vulnerabilities in Multi-modal Retrieval-Augmented Generation
In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025
Pengfei He, Zitao Li, Yue Xing, Yaliang Li, Jiliang Tang, Bolin Ding
Advancing Reasoning with Off-the-Shelf LLMs: A Semantic Structure Perspective
In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025
Kai Guo, Harry Shomer, Shenglai Zeng, Haoyu Han, Yu Wang, Jiliang Tang
Empowering GraphRAG with Knowledge Filtering and Integration
In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025
Harry Shomer, Jiejun Xu
Automated Label Placement on Maps via Large Language Models
In the AI for Data Editing Workshop (AI4DE), KDD, 2025
Yu Song, Zhigang Hua, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu
GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning
In Proceedings of the 34th ACM International on Conference on Information and Knowledge Management (CIKM), 2025
Harry Shomer, Jay Revolinsky, Jiliang Tang
Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion
In Proceedings of 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025
Yingqian Cui, Pengfei He, Jingying Zeng, Hui Liu, Xianfeng Tang, Zhenwei DAI, Yan Han, Chen Luo, Jing Huang, Zhen Li, Suhang Wang, Yue Xing, Jiliang Tang, Qi He
Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models
In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Jie Ren, Zhenwei Dai, Xianfeng Tang, Hui Liu, Jingying Zeng, Zhen Li, Rahul Goutam, Suhang Wang, Yue Xing, Qi He, Hui Liu
A General Framework to Enhance Fine-tuning-based LLM Unlearning
In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Hang Li, Tianlong Xu, Kaiqi Yang, Yucheng Chu, Yanling Chen, Yichi Song, Qingsong Wen, Hui Liu
Ask-Before-Detection: Identifying and Mitigating Conformity Bias in LLM-Powered Error Detector for Math Word Problem Solutions
In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Bo Wang, Weiyi He, Pengfei He, Shenglai Zeng, Zhen Xiang, Yue Xing, Jiliang Tang
Unveiling Privacy Risks in LLM Agent Memory
In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Haoyu Han, Yaochen Xie, Hui Liu, Xianfeng Tang, Sreyashi Nag, William Headden, Yang Li, Chen Luo, Shuiwang Ji, Qi He, Jiliang Tang
Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs' Reasoning
In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Shenglai Zeng, Pengfei He, Kai Guo, Tianqi Zheng, Hanqing Lu, Yue Xing, Hui Liu
Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach
In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Yongjia Lei, Haoyu Han, Ryan A. Rossi, Franck Dernoncourt, Nedim Lipka, Mahantesh M Halappanavar, Jiliang Tang, Yu Wang
Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge Bases
In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Pengfei He, Yupin Lin, Shen Dong, Han Xu, Yue Xing, Hui Liu
Red-Teaming LLM Multi-Agent Systems via Communication Attacks
In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Bingheng Li, Zhikai Chen, Haoyu Han, Shenglai Zeng, Jingzhe Liu, Jiliang Tang
Unveiling Mode Connectivity in Graph Neural Network
In Proceedings of 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025
Yu Song, Zhigang Hua, Harry Shomer, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu
A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation
In Proceedings of 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025
Yingqian Cui*, Jie Ren*, Han Xu, Pengfei He, Hui Liu, Lichao Sun, Yue Xing, Jiliang Tang
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
In ACM SIGKDD Explorations Newsletter, 2025
Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Lingjuan Lyu, Wenqi Fan, Hui Liu, Jiliang Tang
FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models
In ACM SIGKDD Explorations Newsletter, 2025
Yucheng Chu, Peng He, Hang Li, Haoyu Han, Kaiqi Yang, Yu Xue, Tingting Li, Joseph Krajcik, Jiliang Tang
Enhancing LLM-Based Short Answer Grading with Retrieval-Augmented Generation
In Proceedings of the 18th International Conference on Educational Data Mining (EDM), 2025
Jie Ren*, Kangrui Chen*, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu
Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025
Jiayuan Ding*, Jianhui Lin*, Shiyu Jiang*, Yixin Wang, Ziyang Mao, Zhaoyu Fang, Jiliang Tang, Min Li, Xiaojie Qiu
Toward a Privacy-Preserving Predictive Foundation Model of Single-Cell Transcriptomics with Federated Learning and Tabular Modeling
Preprint, 2025
Qiaolin Lu, Jiayuan Ding, Lingxiao Li, Yi Chang
Graph Contrastive Learning of Subcellular-Resolution Spatial Transcriptomics Improves Cell Type Annotation and Reveals Critical Molecular Pathways
In Briefings in Bioinformatics (Volume 26, Issue 1), 2025
Geri Skenderi, Hang Li, Jiliang Tang, Marco Cristani
Graph-level Representation Learning with Joint-Embedding Predictive Architectures
In Transactions on Machine Learning Research (TMLR), 2025
Pengfei He, Yue Xing, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou
Stealthy Backdoor Attack via Confidence-driven Sampling
In Transactions on Machine Learning Research (TMLR), 2025
Zhikai Chen, Han Xie, Jian Zhang, Xiang song, Jiliang Tang, Huzefa Rangwala, George Karypis
AutoG: Towards Automatic Graph Construction from Tabular Data
In Proceedings of International Conference on Learning Representations (ICLR), 2025
Xinnan Dai, Haohao Qu, Yifei Shen, Bohang Zhang, Qihao Wen, Wenqi Fan, Dongsheng Li, Jiliang Tang, Caihua Shan
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
In Proceedings of International Conference on Learning Representations (ICLR), 2025
Pengfei He, Han Xu, Yue Xing, Hui Liu, Makoto Yamada, Jiliang Tang
Data Poisoning for In-context Learning
In Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025
Shenglai Zeng, Jiankun Zhang, Bingheng Li, Yuping Lin, Tianqi Zheng, Dante Everaert, Hanqing Lu, Hui Liu, Hui Liu, Yue Xing, Monica Xiao Cheng, Jiliang Tang
Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective
In Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025
Juanhui Li, Sreyashi Nag, Hui Liu, Xianfeng Tang, Sheikh Muhammad Sarwar, Limeng Cui, Hansu Gu, Suhang Wang, Qi He, Jiliang Tang
Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data
In Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025
Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Kristen Johnson, Jiliang Tang
A Survey to Recent Progress Towards Understanding In-Context Learning
In Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025
Pengfei He, Yingqian Cui, Han Xu, Hui Liu, Makoto Yamada, Jiliang Tang, Yue Xing
Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study
In Stat Special Issue on Statistics for Large Language Models and Large Language Models for Statistics, 2025
Yingqian Cui, Jie Ren, Pengfei He, Jiliang Tang, Yue Xing
Superiority of Multi-Head Attention in In-Context Linear Regression
In Proceedings of The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Yingqian Cui, Pengfei He, Xianfeng Tang, Qi He, Chen Luo, Jiliang Tang, Yue Xing
A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration
In Proceedings of The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Jay Revolinsky*, Harry Shomer*, Jiliang Tang
Towards Understanding Link Predictor Generalizability Under Distribution Shifts
In Proceedings of 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025
Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Wenqi Fan, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li
Graph Machine Learning in the Era of Large Language Models (LLMs)
In ACM Transactions on Intelligent Systems and Technology, 2025
Publications in 2024
Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu C. Aggarwal, Jiliang Tang
Sharpness-Aware Data Poisoning Attack
★ Spotlight: 5% · In Proceedings of International Conference on LearningRepresentations (ICLR), 2024
Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang
Towards Neural Scaling Laws on Graphs
In Proceedings of the 3rd Learning on Graphs Conference (LoG), 2024
Hang Li, Wei Jin, Geri Skenderi, Harry Shomer, Wenzhuo Tang, Wenqi Fan, Jiliang Tang
Sub-graph Based Diffusion Model for Link Prediction
In Proceedings of the 3rd Learning on Graphs Conference (LoG), 2024
Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu
A Pure Transformer Pretraining Framework on Text-attributed Graphs
In Proceedings of the 3rd Learning on Graphs Conference (LoG), 2024
Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
In Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS, Datasets and Benchmarks track), 2024
Li Ma*, Haoyu Han*, Juanhui Li, Harry Shomer, Hui Liu, Xiaofeng Gao, Jiliang Tang
Mixture of Link Predictors
In Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS), 2024
Guangliang Liu, Haitao Mao, Jiliang Tang, Kristen Marie Johnson
Intrinsic Self-correction for Enhanced Morality: An Analysis of Internal Mechanisms and the Superficial Hypothesis
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Han Xu, Jie Ren, Pengfei He, Shenglai Zeng, Yingqian Cui, Amy Liu, Hui Liu, Jiliang Tang
On the Generalization of Training-based ChatGPT Detection Methods
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Yuping Lin, Pengfei He, Han Xu, Yue Xing, Makoto Yamada, Hui Liu, Jiliang Tang
Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Kaiqi Yang, Hang Li, Hongzhi Wen, Tai-Quan Peng, Jiliang Tang, Hui Liu
Are Large Language Models (LLMs) Good Social Predictors?
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Jiayuan Ding, Lingxiao Li, Qiaolin Lu, Julian Venegas, Yixin Wang, Lidan Wu, Wei Jin, Hongzhi Wen, Renming Liu, Wenzhuo Tang, Xinnan Dai, Zhaoheng Li, Wangyang Zuo, Yi Chang, Yu Leo Lei, Lulu Shang, Patrick Danaher, Yuying Xie, Jiliang Tang
SpatialCTD: A Large-Scale Tumor Mfoenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology
In Journal of Computational Biology, Vol. 31, No. 9, 2024
Kaiqi Yang, Haoyu Han, Wei Jin, Hui Liu
Spectral-Aware Augmentation for Enhanced Graph Representation Learning
In Proceedings of the 33rd ACM International on Conference on Information and Knowledge Management (CIKM), 2024
Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective
In Proceedings of 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024
Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang
LPFormer: An Adaptive Graph Transformer for Link Prediction
In Proceedings of 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024
Xiaowei Qian*, Zhimeng Guo*, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark
In Proceedings of 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024
Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang
Source Free Graph Unsupervised Domain Adaptation
In Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM), 2024
Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention
In Proceedings of the 18th European Conference on Computer Vision (ECCV), 2024
Shenglai Zeng*, Yaxin Li*, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin
Exploring Memorization in Fine-tuned Language Models
In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), 2024
Shenglai Zeng*, Jiankun Zhang*, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, Jiliang Tang
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)
In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), 2024
Bingheng Li*, Linxin Yang*, Yupeng Chen, Senmiao Wang, Qian Chen, Haitao Mao, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
Haitao Mao*, Zhikai Chen*, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
Position Paper: Graph Foundation Models
In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective
In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
Lichao Sun, Yue Huang, Haoran Wang, et al
Position Paper: TrustLLM: Trustworthiness in Large Language Models
In Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
Huimin Zou, Jiquan Chen, Xianglan Li, Michael Abraha, Xiangyu Zhao, Jiliang Tang
Modeling Net Ecosystem Exchange of CO2 with Gated Recurrent Unit Neural Networks
In Agricultural and Forest Meteorology, 2024
Jiayuan Ding*, Renming Liu*, Hongzhi Wen*, Wenzhuo Tang*, Zhaoheng Li, Julian Venegas, Runze Su, Dylan Molho, Wei Jin, Yixin Wang, Qiaolin Lu, Lingxiao Li, Wangyang Zuo, Yi Chang, Yuying Xie, Jiliang Tang
DANCE: a deep learning library and benchmark platform for single-cell analysis
In Genome Biology, 2024
Kaiqi Yang, Yucheng Chu, Taylor Darwin, Ahreum Han, Hang Li, Hongzhi Wen, Yasemin Copur-Gencturk, Jiliang Tang, Hui Liu
Content Knowledge Identification with Multi-Agent Large Language Models (LLMs)
In Proceedings of the 25th International Conference on Artificial Intelligence in Education (AIED), 2024
Jie Ren, Han Xu, Yiding Liu, Yingqian Cui, Shuaiqiang Wang, Dawei Yin, Jiliang Tang
A Robust Semantics-based Watermark for Large Language Model against Paraphrasing
In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024
Ziwen Zhao, Yuhua Li, Yixiong Zou, Jiliang Tang, Ruixuan Li
Masked Graph Autoencoder with Non-discrete Bandwidths
In Proceedings of the 33rd Web Conference (TheWebConf), 2024
Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Dawei Yin
Whole Page Unbiased Learning to Rank
In Proceedings of the 33rd Web Conference (TheWebConf), 2024
Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Revisiting Link Prediction: a Data Perspective
In Proceedings of International Conference on LearningRepresentations (ICLR), 2024
Qiaolin Lu*, Jiayuan Ding*, Lingxiao Li, Yi Chang, Jiliang Tang, Xiaojie Qiu
Graph Contrastive Learning of Subcellular-resolution Spatial Transcriptomics Improves Cell Type Annotation and Reveals Critical Molecular Pathways
Preprint, 2024
Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
Label-free Node Classification on Graphs with Large Language Models (LLMs)
In Proceedings of International Conference on LearningRepresentations (ICLR), 2024
Hongzhi Wen*, Wenzhuo Tang*, Xinnan Dai, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang
CellPLM: Pre-training of Cell Language Model Beyond Single Cells
In Proceedings of International Conference on LearningRepresentations (ICLR), 2024
Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada
Structural Fairness-aware Active Learning for Graph Neural Networks
In Proceedings of International Conference on LearningRepresentations (ICLR), 2024
Yaxin Li*, Jie Ren*, Han Xu, Hui Liu
Neural Style Protection: Counteracting Unauthorized Neural Style Transfer
In Winter Conference on Applications of Computer Vision (WACV), 2024
Publications in 2023
Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
In ACM SIGKDD Explorations Newsletter (SIGKDD Explorations), 2023
Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang
Distance-Based Propagation for Efficient Knowledge Graph Reasoning
In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang
Towards Label Position Bias in Graph Neural Networks
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
Juanhui Li*, Harry Shomer*, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
Wei Jin*, Haitao Mao*, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
Zitao Liu, Qiongqiong Liu, Teng Guo, Jiahao Chen, Shuyan Huang, Xiangyu Zhao, Jiliang Tang, Weiqi Luo, Jian Weng
XES3G5M: A Knowledge Tracing Benchmark Dataset with Auxiliary Information
In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
Harry Shomer, Wei Jin, Juanhui Li, Yao Ma, Hui Liu
Learning Representations for Hyper-Relational Knowledge Graphs
In Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2023
Wentao Wang, Harry Shomer, Yuxuan Wan, Yaxin Li, Jiangtao Huang, Hui Liu
A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data
In Proceedings of the 32nd ACM International on Conference on Information and Knowledge Management (CIKM), 2023
Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang
Single-Cell Multimodal Prediction via Transformers
In Proceedings of 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023
Hua Liu, Haoyu Han, Wei Jin, Xiaorui Liu, Hui Liu
Enhancing Graph Representations Learning with Decorrelated Propagation
In Proceedings of 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023
Han Xu, Xiaorui Liu, Wentao Wang, Zitao Liu, Anil K. Jain, Jiliang Tang
How does the Memorization of Neural Networks Impact Adversarial Robust Models?
In Proceedings of 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023
Juanhui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?
In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL), 2023
Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang
Alternately Optimized Graph Neural Networks
In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
Rui Xue, Haoyu Han, MohamadAli Torkamani, Jian Pei, Xiaorui Liu
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
Han Xu, Pengfei He, Jie Ren, Yuxuan Wan, Zitao Liu, Hui Liu, Jiliang Tang
Probabilistic Categorical Adversarial Attack and Adversarial Training
In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang
Adversarial Attacks for Black-box Recommender Systems via Copying Transferable Cross-domain User Profiles
In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023
Wenqi Fan, Chengyi Liu, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li
Generative Diffusion Models on Graphs: Methods and Applications
In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023
Jamell Dacon, Jiliang Tang
Beyond Race and Gender: A Look at Sociodemographic Biases Toward Persons with Disabilities
In Proceedings in the 9th International Conference on Computational Social Science, 2023
Jamell Dacon, Jiliang Tang
Can We Identify and Dismantle ISMs that Plague Our Society: An Online Approach
In Proceedings in the 9th International Conference on Computational Social Science, 2023
Juanhui Li, Yao Ma, Wei Zeng, Suqi Cheng, Jiliang Tang, Shuaiqiang Wang, Dawei Yin
Graph Enhanced BERT for Query Understanding
In Proceedings of 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023
Wenzhuo Tang*, Renming Liu*, Hongzhi Wen, Xinnan Dai, Jiayuan Ding, Hang Li, Wenqi Fan, Yuying Xie, Jiliang Tang
A General Single-Cell Analysis Framework via Conditional Diffusion Generative Models
Preprint, 2023
Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang
Toward Degree Bias in Embedding-Based Knowledge Graph Completion
In Proceedings of the 32nd Web Conference (TheWebConf), 2023
Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah
Empowering Graph Representation Learning with Test-Time Graph Transformation
In Proceedings of International Conference on LearningRepresentations (ICLR), 2023
Jie Ren*, Han Xu*, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang
Transferable Unlearnable Examples
In Proceedings of International Conference on LearningRepresentations (ICLR), 2023
Publications in 2022
Pengfei He, Haochen Liu, Xiangyu Zhao, Hui Liu, Jiliang Tang
PROPN: Personalized Probabilistic Strategic Parameter Optimization in Recommendations
In Proceedings of the 31st ACM International on Conference on Information and Knowledge Management (CIKM), 2022
Haitao Mao*, Lixin Zou*, Xiaokai Chu, Jiliang Tang, Shuaiqiang Wang, Wenwen ye, Dawei yin
A Large Scale Search Dataset for Unbiased Learning to Rank
In Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS), 2022
Wentao Wang, Han Xu, Xiaorui Liu, Yaxin Li, Bhavani Thuraisingham, Jiliang Tang
Imbalanced Adversarial Training with Reweighting
In Proceedings of the 2022 IEEE International Conference on Data Mining, 2022
Jamell Dacon, Haochen Liu, Jiliang Tang
Evaluating and Mitigating Inherent Linguistic Bias of African American English through Inference
In Proceedings in the 29th International Conference on Computational Linguistics, 2022
Jamell Dacon, Harry Shomer, Shaylynn Crum-Dacon, Jiliang Tang
Detecting Harmful Online Conversational Content towards LGBTQIA+ Individuals
In Proceedings of the Queer in AI Workshop at NAACL, 2022
Yiqi Wang, Chaozhuo Li, Zheng Liu, Mingzheng Li, Jiliang Tang, Xing Xie, Lei Chen, Philip S. Yu
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering
In ACM Transactions on Information Systems (TOIS), 2022
Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Ying Bin
Condensing Graphs via One-Step Gradient Matching
In Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022
Wei Jin*, Xiaorui Liu*, Yao Ma, Charu Aggarwal, Jiliang Tang
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective
In Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022
Hongzhi Wen*, Jiayuan Ding*, Wei Jin*, Yuying Xie, Jiliang Tang
Graph Neural Networks for Multimodal Single-Cell Data Integration
In Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022
Jamell Dacon
Towards a Deep Multi-layered Dialectal Language Analysis: A Case Study of African-American English
In Proceedings of the Second Workshop on Bridging Human-Computer Interaction and Natural Language Processing at NAACL (HCI+NLP), 2022
Haochen Liu*, Yiqi Wang*, Wenqi Fan, Xiaorui Liu, Yaxin Li, Shaili Jain, Yunhao Liu, Anil K. Jain, Jiliang Tang
Trustworthy AI: A Computational Perspective
In ACM Transactions on Intelligent Systems and Technology (TIST), 2022
Jamell Dacon, Haochen Liu, Jiliang Tang
Using Inference to Mitigate Linguistic Bias Against African American English
In Proceedings of the 8th International Conference on Computational Social Science (IC2S2), 2022
Jamell Dacon, Jiliang Tang
Examining Word Representations between #BlackLivesMatter Movement and its Counter Protests: 2013 to 2020
In Proceedings of the 8th International Conference on Computational Social Science (IC2S2), 2022
Jamell Dacon
Understanding African American English on a Token-Level Beyond Accuracy
In the 8th International Conference on Computational Social Science (IC2S2), 2022
Wenqi Fan*, Xiaorui Liu*, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li
Graph Trend Filtering Networks for Recommendation
In Proceedings of 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022
Haochen Liu, Joseph Thekinen, Sinem Mollaoglu, Da Tang, Ji Yang, Youlong Cheng, Hui Liu, Jiliang Tang
Toward Annotator Group Bias in Crowdsourcing
In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL), 2022
Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah
Graph Condensation for Graph Neural Networks
In Proceedings of International Conference on LearningRepresentations (ICLR), 2022
Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
Automated Self-Supervised Learning for Graphs
In Proceedings of International Conference on Learning Representations (ICLR), 2022
Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang
Is Homophily a Necessity for Graph Neural Networks
In Proceedings of International Conference on Learning Representations (ICLR), 2022
Haochen Liu, Da Tang, Ji Yang, Xiangyu Zhao, Hui Liu, Jiliang Tang, Youlong Cheng
Rating Distribution Calibration for Selection Bias Mitigation in Recommendations
In Proceedings of the 31st Web Conference (TheWebConf), 2022
Wentao Wang, Joseph Thekinen, Xiaorui Liu, Zitao Liu, Jiliang Tang
Learning from Imbalanced Crowdsourced Labeled Data
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022
Yiqi Wang, Chaozhuo Li, Mingzheng Li, Wei Jin, Yuming Liu, Hao Sun, Xing Xie, Jiliang Tang
Localized Graph Collaborative Filtering
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022
Xiangyu Zhao, Wenqi Fan, Hui Liu, Jiliang Tang
Multi-type Urban Crime Prediction
In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), 2022
Publications in 2021
Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang
Graph Neural Networks with Adaptive Residual
In Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS), 2021
Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang, Xudong Zheng, Xiaobing Liu, Xiwang Yang
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations
In Proceedings of the 21st IEEE International Conference on Data Mining (ICDM), 2021
Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah
A Unified View on Graph Neural Networks as Graph Signal Denoising
In Proceedings of the 2021 ACM on Conference on Information and Knowledge Management (CIKM), 2021
Tyler Derr, Hamid Karimi, Xiaorui Liu, Jiejun Xu, Jiliang Tang
Deep Adversarial Network Alignment
In Proceedings of the 2021 ACM on Conference on Information and Knowledge Management (CIKM), 2021
Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu Aggarwal, Jiliang Tang
Graph Feature Gating Networks
In Proceedings of the 2021 ACM on Conference on Information and Knowledge Management (CIKM), 2021
Haochen Liu, Da Tang, Ji Yang, Xiangyu Zhao, Jiliang Tang, Youlong Cheng
Self-supervised Learning for Alleviating Selection Bias in Recommendation Systems
In International Workshop on Industrial Recommendation Systems at SIGKDD (IRS), 2021
Zhiwei Wang, Zhengzhang Chen, Jingchao Ni, Hui Liu, Haifeng Chen, Jiliang Tang
Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang
Automated Loss Function Search in Recommendations
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang
Graph Adversarial Attack via Rewiring
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
Jamell Dacon, Haochen Liu
Does Gender Matter in the News? Detecting and Examining Gender Bias in News Articles
In Proceedings of the 7th International Conference on Computational Social Science (IC2S2), 2021
Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang
Elastic Graph Neural Networks
In Proceedings of the 38th International Conference on Machine Learning (ICML), 2021
Han Xu, Xiaorui Liu, Yaxin Li, Anil Jain, Jiliang Tang
To be Robust or to be Fair: Towards Fairness in Adversarial Training
In Proceedings of the 38th International Conference on Machine Learning (ICML), 2021
Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification
In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics, Findings of ACL (ACL), 2021
Xiangyu Zhao, Long Xia, Lixin Zou, Dawei Yin, Hui Liu, Jiliang Tang
User Simulation via Supervised Generative Adversarial Network
In Proceedings of the 30th Web Conference (WWW), 2021
Xiangyu Zhao, Haochen Liu, Hui Liu, Jiliang Tang, Weiwei Guo, Jun Shi, Sida Wang, Huiji Gao, Bo Long
Field-aware Embedding Space Searching in Recommender Systems
In Proceedings of the 30th Web Conference (WWW), 2021
Xiaorui Liu, Yao Li, Rongrong Wang, Jiliang Tang, Ming Yan
Linear Convergent Decentralized Optimization with Compression
In Proceedings of the 9th International Conference on Learning Representations (ICLR), 2021
Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu, Jiliang Tang
Yet Meta Learning Can Adapt Fast, It Can Also Break Easily
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2021
Xiangyu Zhao, Changsheng Gu, Haoshenglun Zhang, Xiwang Yang, Xiaobing Liu, Hui Liu, Jiliang Tang
Online Advertising Impression Strategy in Recommender Systems
In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021
Yaxin Li, Wei Jin, Han Xu, Jiliang Tang
DeepRobust: A Platform for Adversarial Attacks and Defenses
In Demonstrations Program of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021
Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang
Node Similarity Preserving Graph Convolutional Networks
In Proceedings of the 14th ACM Conference on Web Search and Data Mining (WSDM), 2021
Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li
CopyAttack: Attacking Black-box Recommendations via Copying Cross-domain User Profiles
In Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE), 2021
Publications in 2020
Aaron Brookhouse*, Tyler Derr*, Hamid Karimi*, H. Russell Bernard, Jiliang Tang
Road to the White House: Analyzing the Relations Between Mainstream and Social Media During the U.S. Presidential Primaries
Preprint, 2020
Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu, Jiliang Tang
Self-supervised Learning on Graphs: Deep Insights and New Direction
Preprint, 2020
Haochen Liu, Zhiwei Wang, Tyler Derr, Jiliang Tang
Chat as Expected: Learning to Manipulate Black-box Neural Dialogue Models
Preprint, 2020
Yiqi Wang*, Yao Ma*, Charu Aggarwal, Jiliang Tang
Customized Graph Neural Networks
Preprint, 2020
Yaxin Li, Wei Jin, Han Xu, Jiliang Tang
DeepRobust: A PyTorch Library for Adversarial Attacksand Defenses
Preprint, 2020
Xiangyu Zhao, Jiliang Tang
Exploring Spatio-Temporal and Cross-Type Correlations for Crime Prediction
Preprint, 2020
Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Jiliang Tang
Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study
In [Repository Code]-->https://github.com/DSE-MSU/DeepRobust, 2020
Haochen Liu, Zitao Liu, Zhongqin Wu, Jiliang Tang
Personalized Multimodal Feedback Generation in Education
In Proceedings of the 28th International Conference on Computational Linguistics (COLING), 2020
Haochen Liu, Jamell Dacon, Wenqi Fan, Hui Liu, Zitao Liu, Jiliang Tang
Does Gender Matter? Towards Fairness in Dialogue Systems
In Proceedings of the 28th International Conference on Computational Linguistics (COLING), 2020
Haochen Liu, Wentao Wang, Yiqi Wang, Hui Liu, Zitao Liu, Jiliang Tang
Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning
In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
Hamid Karimi, Tyler Derr, Kaitlin T. Torphy, Kenneth A. Frank, Jiliang Tang
Understanding and Promoting Teacher Connections in Online Social Media: A Case Study on Pinterest
In Proceedings of the 2020 IEEE International Conference on Engineering, Technology and Education (TALE), 2020
Wentao Wang, Tyler Derr, Yao Ma, Suhang Wang, Hui Liu, Zitao Liu, Jiliang Tang
Learning from Incomplete Labeled Data via Adversarial Data Generation
In Proceedings of the 2020 IEEE International Conference on Data Mining (ICDM), 2020
Juanhui Li*, Yao Ma*, Yiqi Wang, Charu Aggarwal, Chang-Dong Wang, Jiliang Tang
Graph Pooling with Representativeness
In Proceedings of the 2020 IEEE International Conference on Data Mining (ICDM), 2020
Wentao Wang, Guowei Xu, Wenbiao Ding, Gale Yan Huang, Guoliang Li, Jiliang Tang, Zitao Liu
Representation Learning from Limited Educational Data with Crowdsourced Labels
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020
Wenqi Fan, Yao Ma, Qing Li, Jianping Wang, Guoyong Cai, Jiliang Tang, Dawei Yin
A Graph Neural Network Framework for Social Recommendations
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020
Xiangyu Zhao, Long Xia, Lixin Zou, Dawei Yin, Hui Liu, Jiliang Tang
Whole-Chain Recommendations
In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM), 2020
Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji
XGNN: Towards Model-Level Explanations of Graph Neural Networks
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang
Graph Structure Learning for Robust Graph Neural Networks
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
Xiangyu Zhao, Xudong Zheng, Xiwang Yang, Xiaobing Liu, Jiliang Tang
Jointly Learning to Recommend and Advertise
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
Haochen Liu*, Xiangyu Zhao*, Chong Wang, Xiaobing Liu, Jiliang Tang
Automated Embedding Size Search in Deep Recommender Systems
In Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020
Hamid Karimi*, Tyler Derr*, Jiangtao Huang, Jiliang Tang
Online Academic Course Performance Prediction using Relational Graph Convolutional Neural Network
In Proceedings of 13th International Conference on Educational Data Mining (EDM), 2020
Hamid Karimi, Kaitlin T. Torphy, Tyler Derr, Kenneth A. Frank, Jiliang Tang
Characterizing Teacher Connections in Online Social Media: A Case Study on Pinterest
In proceedings of 2020 Annual ACM Conference on Learning at Scale, 2020
Hang Li, Zhiwei Wang, Jiliang Tang, Wenbiao Ding, Zitao Liu
Siamese Neural Networks for Class Activity Detection
In Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED), 2020
Hamid Karimi, Tyler Derr, Kaitlin T. Torphy, Kenneth A. Frank, Jiliang Tang
Towards Improving Sample Representativeness of Teachers on Online Social Media: A Case Study on Pinterest
In Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED), 2020
Gale Yan Huang, Jiahao Chen, Haochen Liu, Weiping Fu, Wenbiao Ding, Jiliang Tang, Songfan Yang, Zitao Liu
Neural Multi-Task Learning for Teacher Question Detection in Online Classrooms
In Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED), 2020
Tyler Derr, Zhiwei Wang, Jamell Dacon, Jiliang Tang
Link and Interaction Polarity Predictions in Signed Networks
In Social Network Analysis and Mining. 10. 2020 (18), 2020
Christina B.Azodi, Jiliang Tang, Shin-Han Shiu
Opening the Black Box: Interpretable Machine Learning for Geneticists
In Trends in Genetics, 2020
Jie Zhuang, Tai-quan (Winson) Peng, Jiliang Tang, Yingcai Wu
Mixed and Blended Emotional Reactions to 2014 Ebola Outbreak
In Journal of Global Health, 2020
Saket Sathe, Sayani Aggarwal, Jiliang Tang
Gene Expression and Protein Function: A Survey of Deep Learning Methods
In ACM SIGKDD Explorations, 2020
Xiaorui Liu, Yao Li, Jiliang Tang, Ming Yan
A Double Residual Compression Algorithm for Efficient Distributed Learning
In International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Xiaoyang Wang, Yao Ma, Yiqi Wang, Wei Jin, Xin Wang, Jiliang Tang
Traffic Flow Prediction via Spatial Temporal Graph Neural Network
In Proceedings of the World Wide Web Conference (WWW), 2020
Amin Javari, Tyler Derr, Pouya Esmailian, Jiliang Tang, Kevin Chen-Chuan Chang
ROSE: Role-based Signed Network Embedding
In Proceedings of the World Wide Web Conference (WWW), 2020
Wenqi Fan, Yao Ma, Han Xu, Xiaorui Liu, Jianping Wang, Qing Li, Jiliang Tang
Deep Adversarial Canonical Correlation Analysis
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2020
Wentao Wang, Suhang Wang, Wenqi Fan, Zitao Liu, Jiliang Tang
Global-and-Local Aware Data Generation for the Class Imbalance Problem
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2020
Teng Guo, Feng Xia, Shihao Zhen, Xiaomei Bai, Dongyu Zhang, Zitao Liu, Jiliang Tang
Graduate Employment Prediction with Bias
In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020
Zhiwei Wang, Hui Liu, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu
Learning Multi-level Dependencies for Robust Word Recognition
In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020
Tyler Derr
Network Analysis with Negative Links
In Proceedings of the International Conference on Web Search and Data Mining (WSDM), 2020
Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu Aggarwal, Jiliang Tang
Epidemic Graph Convolutional Network
In Proceedings of the Thirteenth ACM International Conference on Web Search and Data Mining (WSDM), 2020
Yao Ma, Ziyi Guo, Zhaochun Ren, Eric Zhao, Jiliang Tang, Dawei Yin
Streaming Graph Neural Networks
In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020
Publications in 2019
Hamid Karimi, Tyler Derr, Jiliang Tang
Characterizing the Decision Boundary of Deep Neural Networks
Preprint, 2019
Haochen Liu, Tyler Derr, Zitao Liu, Jiliang Tang
Say what I want: Towards the dark side of neural dialogue models
Preprint, 2019
Zhiwei Wang, Yao Ma, Zitao Liu, Jiliang Tang
R-Transformer: Recurrent Neural Network Enhanced Transformer
Preprint, 2019
Suhas Ranganath, Xia Hu, Jiliang Tang, Suhang Wang, Huan Liu
Understanding and Identifying Rhetorical Questions in Social Media
In ACM Transactions on Intelligent Systems and Technology (TIST), 2019
Ghazaleh Beigi, Jiliang Tang, Huan Liu
Social Science-guided Feature Engineering: A Novel Approach to Signed Link Analysis
In ACM Transactions on Intelligent Systems and Technology (TIST), 2019
Zhiwei Wang, Xiaorui Liu, Jiliang Tang, Dawei Yin
Weight Loss Prediction in Social-Temporal Context
In IEEE International Conference on Healthcare Informatics (ICHI), 2019
Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang, Qing Li
Deep Adversarial Social Recommendation
In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI), 2019
Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang, Qing Li
Deep Social Collaborative Filtering
In Proceedings of the 13th ACM Conference on Recommender Systems (RecSys), 2019
Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil Jain
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
In International Journal of Automation and Computing (IJAC), 2019
Hamid Karimi, Tyler Derr, Aaron Brookhouse, Jiliang Tang
Multi-Factor Congressional Vote Prediction
In International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2019
Tyler Derr, Cassidy Johnson, Yi Chang, Jiliang Tang
Balance in Signed Bipartite Networks
In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM), 2019
Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang
Graph Convolutional Networks with EigenPooling
In Proceedings of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019
Xiangyu Zhao, Long Xia, Jiliang Tang, Dawei Yin
Deep Reinforcement Learning for Search, Recommendation and Online Advertising: A Survey
In ACM SIGWEB Newsletter (SIGWEB), 2019
Hamid Karimi, Jiliang Tang
Learning Hierarchical Discourse-level Structure for Fake News Detection
In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HTL), 2019
Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, Dawei Yin
Graph Neural Networks for Social Recommendation
In Proceedings of the Web Conference (WWW), 2019
Tianqiao Liu, Zhiwei Wang, Jiliang Tang, Songfan Yang, Zitao Liu
Recommender Systems with Heterogeneous Side Information
In Proceedings of the 28th International Conference on World Wide Web (WWW), 2019
Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang
Multi-dimensional Graph Convolutional Networks
In Proceedings of the Nineteenth SIAM International Conference on Data Mining (SDM), 2019
Guowei Xu, Wenbiao Ding, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu
Learning Effective Embeddings from Crowdsourced Labels: An Educational Case Study
In Proceedings of IEEE International Conference on Data Engineering (ICDE), 2019
Xiangyu Zhao, Liang Zhang, Zhuoye Ding, Dawei Yin, Yihong Zhao, Jiliang Tang
Deep Reinforcement Learning for List-wise Recommendations
In 1st Workshop on Deep Reinforcement Learning for Knowledge Discover (DRL4KDD), 2019
Publications in 2018
Hamid Karimi, Courtland VanDam, Liyang Ye, Jiliang Tang
End-to-End Compromised Account Detection
★ Best Paper Award · In IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018
Zhiwei Wang, Yao Ma, Dawei Yin, Jiliang Tang
Linked Recurrent Neural Networks
Preprint, 2018
Tyler Derr, Jiliang Tang
Congressional Vote Analysis Using Signed Networks
In International Conference on Data Mining Workshops (ICDMW), 2018
Hamid Karimi, Jiliang Tang, Yanen Li
Toward End-to-End Deception Detection in Videos
In Proceedings of the 5th IEEE International Conference on Big Data, 2018
Tyler Derr, Yao Ma, Jiliang Tang
Signed Graph Convolutional Networks
In IEEE International Conference on Data Mining (ICDM), 2018
Tyler Derr, Charu Aggarwal, Jiliang Tang
Signed Network Modeling Based on Structural Balance Theory
In Proceedings of the 2018 ACM on Conference on Information and Knowledge Management (CIKM), 2018
Xiangyu Zhao, Long Xia, Liang Zhang, Zhuoye Ding, Dawei Yin, Jiliang Tang
Deep Reinforcement Learning for Page-wise Recommendations
In Proceedings of the 12th ACM Recommender Systems Conference, 2018
Tyler Derr, Chenxing Wang, Suhang Wang, Jiliang Tang
Relevance Measurements in Online Signed Social Networks
In ACM SIGKDD 14th International Workshop on Mining and Learning with Graphs (MLG), 2018
Xiangyu Zhao, Liang Zhang, Zhuoye Ding, Long Xia, Jiliang Tang, Dawei Yin
Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning
In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Xiangyu Zhao, Jiliang Tang
Crime in Urban Areas: A Data Mining Perspective
In ACM SIGKDD Explorations Newsletter, 2018
Hamid Karimi
Interpretable Multimodal Deception Detection in Videos
In Proceedings of the ACM International Conference on Multimodal Interaction, 2018
Tyler Derr, Zhiwei Wang, Jiliang Tang
Opinions Power Opinions: Joint Link and Interaction Polarity Predictions in Signed Networks
In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018
Yao Ma, Suhang Wang, Jiliang Tang
Local and Global Information Preserved Network Embedding
In IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018
Courtland VanDam, Pang-Ning Tan, Jiliang Tang, Hamid Karimi
CADET: A Multi-View Learning Framework for Compromised Account Detection on Twitter
In IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018
Hamid Karimi, Proteek Roy, Sari Saba-Sadiya, Jiliang Tang
Multi-Source Multi-Class Fake News Detection
In Proceedings of the 27th International Conference on Computational Linguistics, 2018
Yao Ma, Jiliang Tang, Charu Aggarwal
Feature Engineering for Data Streams
In Feature Engineering for Machine Learning and Data Analytics (CRC Press), 2018
Yao Ma, Zhaochun Ren, Ziheng Jiang, Jiliang Tang, Dawei Yin
Multidimensional Network Embedding with Hierarchical Structures
In Proceedings of the 11th ACM Conference on Web Search and Data Mining 2018 (WSDM), 2018
Hongshen Chen, Zhaochun Ren, Jiliang Tang, Yihong Eric Zhao, Dawei Yin
Hierarchical Variational Memory Network for Dialogue Generation
In Proceedings of the 27th International Conference on World Wide Web (WWW), 2018
Jundong Li, Jiliang Tang, Yilin Wang, Yali Wan, Yi Chang, Huan Liu
Understanding and Predicting Delay in Reciprocal Relations
In Proceedings of the 27th International Conference on World Wide Web (WWW), 2018
Tian Xie, Chi-Yu Li, Guan-Hua Tu, Jiliang Tang
How Voice Service Threatens Cellular-connected IoT Devices in the Operational 4G LTE Networks
In IEEE ICC Communication and Information Systems Security Symposium, 2018
Makoto Yamada, Jiliang Tang et al
Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018
Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu
Exploring Hierarchical Structures for Recommender Systems
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018
Hongshen Chen, Xiaorui Liu, Dawei Yin, Jiliang Tang
A Survey on Dialogue Systems: Recent Advances and New Frontiers
In SIGKDD Explorations, 2018
Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu
CrossFire: Cross Media Joint Friend and Item Recommendations
In Proceedings of the 11th ACM Conference on Web Search and Data Mining 2018 (WSDM), 2018
Meizi Zhou, Zhuoye Ding, Jiliang Tang, Dawei Yin
Micro Behaviors: A New Perspective in E-commerce Recommender Systems
In Proceedings of the 11th ACM Conference on Web Search and Data Mining 2018 (WSDM), 2018
Zihan Wang, Ziheng Jiang, Zhaochun Ren, Jiliang Tang, Dawei Yin
A Path-constrained Framework for Discriminating Substitutable and Complementary Products in E-commerce
In Proceedings of the 11th ACM Conference on Web Search and Data Mining 2018 (WSDM), 2018
Yilin Wang, Suhang Wang, Guojun Qi, Jiliang Tang, Baoxin
Weakly Supervised Facial Attribute Manipulation via Deep Adversarial Network
In IEEE Winter Conf. on Applications of Computer Vision (WACV), 2018
Publications in 2017
Zhiwei Wang, Tyler Derr, Dawei Yin, Jiliang Tang
Understanding and Predicting Weight Loss with Mobile Social Networking Data
In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017
Xiangyu Zhao, Dawei Yin, Jiliang Tang
Modeling Temporal-Spatial Correlation for Crime Predictions
In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017
Suhang Wang, Charu Aggarwal, Jiliang Tang, Huan Liu
Attributed Signed Network Embedding
In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017
Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang, Huan Liu
Attributed Network Embedding for Learning in a Dynamic Environment
In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017
Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, Huan Liu
Fake News Detection on Social Media: A Data Mining Perspectives
In SIGKDD Explorations, 2017
Yang Li, Quan Pan, Tao Yang, Suhang Wang, Jiliang Tang, Erik Cambria
Learning Word Representations for Sentiment Analysis
In Cognitive Computation, 2017
Courtland VanDam, Jiliang Tang, Pang-ning Tan
Understanding Compromised Accounts on Twitter
In IEEE/WIC/ACM International Conference on Web Intelligence (WI), 2017
Guo-Jun Qi, Jiliang Tang, Jingdong Wang, Jiebo Luo
Mixture Factorized Ornstein-Uhlenbeck Processes for Time-Series Forecasting
In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017
Yuening Hu, Changsung Kang, Jiliang Tang, Dawei Yin, Yi Chang
Large-scale Location Prediction for Web Pages
In IEEE Trans on Knowledge and Data Engineering (TKDE), 2017
Jundong Li, Jiliang Tang, Huan Liu
Reconstruction-based Unsupervised Feature Selection: An Embedded Approach
In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017
Suhas Ranganth, Suhang Wang, Xia Hu, Jiliang Tang, Huan Liu
Facilitating Time Critical Information Seeking in Social Media
In IEEE Trans on Knowledge and Data Engineering (TKDE), 2017
Jundong Li, Jiliang Tang, Huan Liu
Recent Advances in Feature Selection: A Data Perspective
In Tutorial in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017
Lin Chen, Jiliang Tang, Baoxin Li
Supervised Feature Selection for Multi-class Data
In Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM), 2017
Suhang Wang, Yilin Wang, Jiliang Tang, Charu Aggarwal, Suhas Ranganath, Huan Liu
Exploiting Hierarchical Structures for Unsupervised Feature Selection
In Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM), 2017
Suhang Wang, Jiliang Tang, Charu Aggarwal, Yi Chang, Huan Liu
Signed Network Embedding in Social Media
In Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM), 2017
Yang Li, Suhang Wang, Quan Pan, Tao Yang, Jiliang Tang
Price Recommendation on Vacation Rental Websites
In Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM), 2017
Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert P. Trevino, Jiliang Tang, Huan Liu
Feature Selection: A Data Perspective, [scikit-feature (An Open-Sourced Feature Selection Repo in Python)]
In ACM Computing Surveys (CSUR), 2017
Yilin Wang, Jiliang Tang, Jundong Li, Baoxin Li, Yali Wan, Clayton Mellina, Neil O'Hare, Yi Chang
Understanding and Discovering Deliberate Self-harm Content in Social Media
In Proceedings of International World Wide Web Conference (WWW), 2017
Shiyu Chang, Yang Zhang, Jiliang Tang, Dawei Yin, Yi Chang, Mark Hasegawa-Johnson, Thomas Huang
Streaming Recommender Systems
In Proceedings of International World Wide Web Conference (WWW), 2017
Suhang Wang, Yilin Wang, Jiliang Tang, Kai Shu, Suhas Ranganath, Huan Liu
What Your Images Reveal: Exploiting Visual Contents for Point-of-Interest Recommendation
In Proceedings of International World Wide Web Conference (WWW), 2017
Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani, Huan Liu
User Identity Linkage across Online Social Netwroks: A Review
In ACM SIGKDD Explorations, 2017
Kewei Cheng, Jundong Li, Jiliang Tang, Huan Liu
Unsupervised Sentiment Analysis with Signed Social Networks
In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI), 2017
Yilin Wang, Suhang Wang, Jiliang Tang, Guojun Qi, Huan Liu, Baoxin Li
CLARE:A Joint Approach to Label Classification and Tag Recommendation
In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI), 2017
Lu Jiang, Yannis Kalantidis, Liangliang Cao, Sachin Farfade, Jiliang Tang, Alex Hauptmann
Delving Deep into Personal Photo and Video Search
In the 10th International Conference on Web Search and Data Mining (WSDM), 2017
Publications in 2016
Huan Liu, Fred Morstatter, Jiliang Tang, Reza Zafarani
The Good, the Bad and the Ugly: Uncovering Novel Research Opportunities in Social Media Mining
In International Journal of Data Science and Analytics, 2016
Yunlong He, Jiliang Tang, Hua Ouyang, Changsung Kang, Dawei Yin, Yi Chang
Learning to Rewrite Queries
In Proceedings of 25th ACM Conference on Information and Knowledge Management (CIKM), 2016
Suhang Wang, Jiliang Tang, Fred Morstatter, Huan Liu
Paired Restricted Boltzmann Machine for Linked Data
In Proceedings of 25th ACM Conference on Information and Knowledge Management (CIKM), 2016
Suhang Wang, Jiliang Tang, Charu Aggarwal, Huan Liu
Linked Document Embedding for Classification
In Proceedings of 25th ACM Conference on Information and Knowledge Management (CIKM), 2016
Jiliang Tang, Yi Chang, Charu Aggarwal, Huan Liu
A Survey of Signed Network Mining in Social Media
In To appear in ACM Computing Surveys, 2016
Dawei Yin, Yuening Hu, Jiliang Tang, Tim Daly Jr, Mianwei Zhou, Hua Ouyang, Jianhui Chen, Changsung Kang, Hongbo Deng, Chikashi Nobata, Jean-Marc Langlois, Yi Chang
Ranking Relevance in Yahoo Search
In Proceedings of the 22nd annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016
Shiyu Chang, Yang Zhang, Jiliang Tang, Dawei Yin, Yi Chang, Mark Hasegawa-Johnson, Thomas S. Huang
Positive-Unlabeled Learning in Streaming Networks
In Proceedings of the 22nd annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016
Ruifang He, Yang Liu, Guangchuan Yu, Jiliang Tang, Qinghua Hu, Jianwu Dang
Twitter Summarization with Social-Temporal Context
In To appear in World Wide Web Journal, 2016
Yi Chang, Jiliang Tang, Dawei Yin, Makoto Yamada, Yan Liu
Timeline Summarization with Life Cycle Models from Social Media
In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016
Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu, Baoxin Li
PPP: Joint Pointwise and Pairwise Image Label Prediction
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Ruifang He, Jiliang Tang, Pinghua Gong, Qinghua Hu, Bo Wang
Multi-document Summarization via Group Sparse Learning
In Information Sciences, 2016
Ghazaleh Beigi, Jiliang Tang, Huan Liu
Signed Link Analysis in Social Media Networks
In The 10th International AAAI Conference on Weblogs and Social Media (ICWSM), 2016
Suhas Ranganth, Xia Hu, Jiliang Tang, Suhang Wang, Huan Liu
Identifying Rhetorical Questions in Social Media
In The 10th International AAAI Conference on Weblogs and Social Media (ICWSM), 2016
Pritam Gundecha, Jiliang Tang, Xia Hu, Huan Liu
Exploring Personal Attributes from Unprotected Interactions
In The 10th International AAAI Conference on Weblogs and Social Media， 2016 (ICWSM), 2016
Jiliang Tang, Charu Aggarwal, Huan Liu
Node Classification in Signed Social Networks
In SIAM International Conference on Data Mining (SDM), 2016
Ghazaleh Beigi, Jiliang Tang, Suhang Wang, Huan Liu
Exploiting Emotional Information for Trust/Distrust Prediction
In SIAM International Conference on Data Mining (SDM), 2016
Jiliang Tang, Charu Aggarwal, Huan Liu
Recommendations in Signed Social Networks
In The 25nd International World Wide Web Conference (WWW), 2016
Suhas Ranganath, Xia Hu, Jiliang Tang, Huan Liu
Understanding and Identifying Advocates of Political Campaigns on Social Media
In ACM International Conference on Web Search and Data Mining (WSDM), 2016
Suhas Ranganath, Fred Morstatter, Xia Hu, Jiliang Tang, Suhang Wang, Huan Liu
Predicting Online Protest Participation of Social Media Users
In The AAAI Conference on Artificial Intelligence (AAAI), 2016
Jiliang Tang, SuhangWang, Xia Hu, Dawei Yin, Yingzhou Bi, Yi Chang, Huan Liu
Recommendation with Social Dimensions
In The AAAI Conference on Artificial Intelligence (AAAI), 2016
Publications in 2015
Jiliang Tang, Huan Liu
Trust in Social Media
In Morgan Claypool & Publishers, 2015
Suhang Wang, Jiliang Tang, Huan Liu
Feature Selection
In Encyclopedia of Machine Learning and Data Mining, 2015
Jiliang Tang, Huiji Gao, Atish Das Sarma, Yingzhou Bi, Huan Liu
Trust Evolution: Modeling and Its Applications
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2015
Suhas Ranganath, Suhang Wang, Xia Hu, Jiliang Tang, Huan Liu
Facilitating Time-Critical Information Seeking in Social Media
In The IEEE International Conference on Data Mining (ICDM), 2015
Yunzhong Liu, Yi Chen, Jiliang Tang, Huan Liu
Context-Aware Experience Extraction from Online Health Forums
In IEEE International Conference on Healthcare Informatics (ICHI), 2015
Suhang Wang, Jiliang Tang, Huan Liu
Toward Dual Roles of Users in Recommender Systems
In ACM International Conference of Information and Knowledge Management (CIKM), 2015
Jundong Li, Xia Hu, Jiliang Tang, Huan Liu
Unsupervised Streaming Feature Selection in Social Media
In ACM International Conference of Information and Knowledge Management (CIKM), 2015
Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu Aggarwal, Thomas Huang
Heterogeneous Network Embedding via Deep Architectures
In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015
Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu
Exploring Implicit Hierarchical Structures for Recommender Systems
In International Joint Conference on Artificial Intelligence (IJCAI), 2015
Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu, Baoxin Li
Unsupervised Sentiment Analysis for Social Media Images
In International Joint Conference on Artificial Intelligence, 2015 [Project Webpage] (IJCAI), 2015
Jiliang Tang, Chikashi Nobata, Anlei Dong, Yi Chang, Huan Liu
Propagation-based Sentiment Analysis for Microblogging Data
In SIAM International Conference on Data Mining (SDM), 2015
Suhang Wang, Jiliang Tang, Huan Liu
Embedded Unsupervised Feature Selection
In The AAAI Conference on Artificial Intelligence (AAAI), 2015
Huiji Gao, Jiliang Tang, Xia Hu, Huan Liu
Content-Aware Point of Interest Recommendation on Location-Based Social Networks
In The AAAI Conference on Artificial Intelligence (AAAI), 2015
Suhas Ranganath, Jiliang Tang, Xia Hu, Hari Sundaram, Huan Liu
Leveraging Social Foci for Information Seeking in Social Media
In The AAAI Conference on Artificial Intelligence (AAAI), 2015
Ying Wang, Xin Wang, Jiliang Tang, Wanli Zuo, Guoyong Cai
Modeling Status Theory in Trust Prediction
In The AAAI Conference on Artificial Intelligence (AAAI), 2015
Jiliang Tang, Shiyu Chang, Charu Aggarwal, Huan Liu
Negative Link Prediction in Social Media, [Slides]
In Proceedings of the Eighth ACM International Conference on Web Search and Data Mining (WSDM), 2015
Publications in 2014
Mohammad Ali Abbasi, Jiliang Tang, Huan Liu
Trust Aware Recommender Systems
In Machine Learning book on computational trust, Chapman and Hall/CRC Press, 2014
Jiliang Tang, Salem Alelyani, Huan Liu
Feature Selection for Classification: A Review
In Data Classification: Algorithms and Applications. Editor: Charu Aggarwal, CRC Press, 2014
Pritam Gundecha, Geoffrey Barbier, Jiliang Tang, Huan Liu
User Vulnerability and its Reduction on a Social Networking Site
In ACM Transactions on Knowledge Discovery from Data (TKDD), 2014
Jiliang Tang, Huan Liu
An Unsupervised Feature Selection Framework for Social Media Data
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2014
Jiliang Tang, Huan Liu
Feature Selection for Social Media Data
In ACM Transactions on Knowledge Discovery from Data (TKDD), 2014
Huiji Gao, Jiliang Tang, Huan Liu
Solving the Cold Start Problem in Location Recommendation with Geo-Social Correlations
In Data mining and Knowledge Discovery (DMKD), 2014
Huiji Gao, Jiliang Tang, Huan Liu
Personalized Location Recommendation on Location-based Social Network
In Tutorial on The ACM Recommender System conference (Recsys), 2014
Jiliang Tang, Jie Tang, Huan Liu
Recommendation in Social Media - Recent Advances and New Frontier
In Tutorial on 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2014
Jiliang Tang, Huan Liu
Trust in Social Computing
In Tutorial on the 23nd International World Wide Web Conference (WWW), 2014
Xia Hu, Jiliang Tang, Huiji Gao, Huan Liu
Social Spammer Detection with Sentiment Information
In IEEE International Conference on Data Mining (ICDM), 2014
Jiliang Tang, Xia Hu, Yi Chang, Huan Liu
Predictability of Distrust with Interaction Data
In ACM International Conference on Information and Knowledge Management (CIKM), 2014
Jiliang Tang, Xia Hu, Huan Liu
Is Distrust the Negation of Trust? The Value of Distrust in Social Media
In ACM Hypertext conference (HT), 2014
Mohammad Ali Abbasi, Reza Zafarani, Jiliang Tang, Huan Liu
Am I More Similar to My Followers or Followees? Homophily Effect in Directed Online Social Networks
In ACM Hypertext conference (HT), 2014
Mohammad Ali Abbasi, Jiliang Tang, Huan Liu
Scalable Learning of Users' Preferences Using Networked Data
In ACM Hypertext conference (HT), 2014
Guoyong Cai, Jiliang Tang, Yiming Wen
Trust Prediction with Temporal Dynamics
In Web-Age Information Management, 2014
Xia Hu, Jiliang Tang, Huan Liu
Leveraging Knowledge across Media for Spammer Detection in Microblogging
In Proceedings of the 37th Annual ACM SIGIR Conference, 2014. (SIGIR), 2014
Xia Hu, Jiliang Tang, Huan Liu
Online Social Spammer Detection
In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI), 2014
Jiliang Tang, Xia Hu, Huiji Gao, Huan Liu
Discriminant Analysis for Unsupervised Feature Selection
In The 14th SIAM International Conference on Data Mining (SDM), 2014
Publications in 2013
Salem Alelyani, Jiliang Tang, Huan Liu
Feature Selection for Clustering: A Review
In Data Clustering: Algorithms and Applications, Editor: Charu Aggarwal and Chandan Reddy, CRC Press., 2013
Jiliang Tang, Yi Chang, Huan Liu
Mining Social Media with Social Theories: A Survey
In SIGKDD Explorations, 2013
Jiliang Tang, Xia Hu, Huan Liu
Social Recommendation: A Review
In Social Network Analysis and Mining (SNAM), 2013
Huiji Gao, Jiliang Tang, Xia Hu, Huan Liu
Modeling Temporal Effects of Human Mobile Behavior on Location-Based Social Networks
In ACM International Conference on Information and Knowledge Management (CIKM), 2013
Jiliang Tang, Huiji Gao, Xia Hu, Huan Liu
Context-Aware Review Helpfulness Rating Prediction
In The ACM Conference Series on Recommender Systems (RecSys), 2013
Huiji Gao, Jiliang Tang, Xia Hu, Huan Liu
Exploring Temporal Effects for Location Recommendation on Location-Based Social Networks
In The ACM Conference Series on Recommender Systems (RecSys), 2013
Huiji Gao, Xufei Wang, Jiliang Tang, Huan Liu
Network Denoising in Social Media
In The 2013 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM), 2013
Jiliang Tang, Xia Hu, Huiji Gao, Huan Liu
Exploiting Local and Global Social Context for Recommendation
In The 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013
Xia Hu, Jiliang Tang, Yanchao Zhang, Huan Liu
Social Spammer Detection in Microblogging
In The 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013
Xia Hu, Jiliang Tang, Huiji Gao, Huan Liu
Unsupervised Sentiment Analysis with Emotional Signals
In The 22nd International World Wide Web Conference (WWW), 2013
Jiliang Tang, Huan Liu
CoSelect: Feature Selection with Instance Selection for Social Media Data
In The 13th SIAM International Conference on Data Mining (SDM), 2013
Jiliang Tang, Xia Hu, Huiji Gao, Huan Liu
Unsupervised Feature Selection for Multi-view Data in Social Media
In The 13th SIAM International Conference on Data Mining (SDM), 2013
Xia Hu, jiliang Tang, Huiji Gao, Huan Liu
ActNeT: Active Learning for Networked Texts in Microblogging
In The 13th SIAM International Conference on Data Mining (SDM), 2013
Jiliang Tang, Huiji Gao, Xia Hu, Huan Liu
Exploiting Homophily Effect for Trust Prediction
In the 6th ACM International Conference on Web Search and Data Mining (WSDM), 2013
Xia Hu, Lei Tang, Jiliang Tang, Huan Liu
Exploiting Social Relations for Sentiment Analysis in Microblogging
In The 6th ACM International Conference on Web Search and Data Mining (WSDM), 2013
Publications in 2012
Huiji Gao, Jiliang Tang, Huan Liu
gSCorr: Modeling Geo-Social Correlations for New Check-ins on Location-Based Social Networks
In ACM International Conference on Information and Knowledge Management (CIKM), 2012
Huiji Gao, Jiliang Tang, Huan Liu
Mobile Location Prediction in Spatio-Temporal Context
In Nokia Mobile Data Challenge Workshop, 2012
Jiliang Tang, Huan Liu
Unsupervised Feature Selection for Linked Social Media Data, [Video]
In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD), 2012
Jiliang Tang, Huiji Gao, Huan Liu, Atish Das Sarma
eTrust: Understanding Trust Evolution in an Online World, [Video]
In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD), 2012
Huiji Gao, Jiliang Tang, Huan Liu
Exploring Social-Historical Ties on Location-Based Social Networks
In The Sixth International AAAI Conference on Weblogs and Social Media (ICWSM), 2012
Jiliang Tang, Huan Liu
Feature Selection with Linked Data in Social Media
In SIAM International Conference on Data Mining (SDM), 2012
Jiliang Tang, Huiji Gao, Huan Liu
mTrust: Discerning Multi-Faceted Trust in a Connected World
In The 5th ACM International Conference on Web Search and Data Mining (WSDM), 2012
Jiliang Tang, Xufei Wang, Huiji Gao, Xia Hu, Huan Liu
Enriching Short Texts Representation in MicroBlog for Clustering, [Dataset]
In Journal `Frontiers of Computer Science`, 2012
Publications in 2011
Jiliang Tang, Xufei Wang, Huan Liu
Integrating Social Media Data for Community Detection
In MSM-MUSE, 2011
Xufei Wang, Jiliang Tang, Huan Liu
Document Clustering via Matrix Representation
In The 11th IEEE International Conference on Data Mining (ICDM), 2011