The Untold Secrets of Operational Wi-Fi Calling Services: Vulnerabilities, Attacks, and Countermeasures. - Tian Xie 001; Guan-Hua Tu; Bangjie Yin; Chi-Yu Li 001; Chunyi Peng 001; Mi Zhang 002; Hui Liu 031; Xiaoming Liu 002 (CoRR, 2018)

Learning Multi-Level Dependencies for Robust Word Recognition. - Zhiwei Wang 001; Hui Liu 031; Jiliang Tang; Songfan Yang; Gale Yan Huang; Zitao Liu 001 (AAAI, 2020)

Whole-Chain Recommendations. - Xiangyu Zhao 001; Long Xia; Lixin Zou; Hui Liu 031; Dawei Yin; Jiliang Tang (CIKM, 2020)

Does Gender Matter? Towards Fairness in Dialogue Systems. - Haochen Liu; Jamell Dacon; Wenqi Fan; Hui Liu 031; Zitao Liu 001; Jiliang Tang (COLING, 2020)

Sequence Learning with Side Dependencies. - Zhiwei Wang 001; Hui Liu 031; Gale Yan Huang; Zitao Liu 001 (DSAA, 2020)

Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning. - Haochen Liu; Wentao Wang 006; Yiqi Wang 001; Hui Liu 031; Zitao Liu 001; Jiliang Tang (EMNLP (1), 2020)

Learning from Incomplete Labeled Data via Adversarial Data Generation. - Wentao Wang 006; Tyler Derr; Yao Ma 001; Suhang Wang; Hui Liu 031; Zitao Liu 001; Jiliang Tang (ICDM, 2020)

Memory-efficient Embedding for Recommendations. - Xiangyu Zhao 001; Haochen Liu; Hui Liu 031; Jiliang Tang; Weiwei Guo; Jun Shi; Sida Wang 002; Huiji Gao; Bo Long (CoRR, 2020)

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. - Han Xu 002; Yao Ma 001; Haochen Liu; Debayan Deb; Hui Liu 031; Jiliang Tang; Anil K. Jain 001 (Int. J. Autom. Comput., 2020)

DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems. - Xiangyu Zhao 001; Changsheng Gu; Haoshenglun Zhang; Xiwang Yang; Xiaobing Liu; Jiliang Tang; Hui Liu 031 (AAAI, 2021)

Attacking Black-box Recommendations via Copying Cross-domain User Profiles. - Wenqi Fan; Tyler Derr; Xiangyu Zhao 001; Yao Ma 001; Hui Liu 031; Jianping Wang 001; Jiliang Tang; Qing Li 001 (ICDE, 2021)

AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations. - Xiangyu Zhao 001; Haochen Liu; Wenqi Fan; Hui Liu 031; Jiliang Tang; Chong Wang; Ming Chen; Xudong Zheng; Xiaobing Liu; Xiwang Yang (ICDM, 2021)

Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection. - Zhiwei Wang 001; Zhengzhang Chen; Jingchao Ni; Hui Liu 031; Haifeng Chen; Jiliang Tang (KDD, 2021)

AutoLoss: Automated Loss Function Search in Recommendations. - Xiangyu Zhao 001; Haochen Liu; Wenqi Fan; Hui Liu 031; Jiliang Tang; Chong Wang (KDD, 2021)

Yet Meta Learning Can Adapt Fast, it Can Also Break Easily. - Han Xu 002; Yaxin Li 001; Xiaorui Liu; Hui Liu 031; Jiliang Tang (SDM, 2021)

AutoDim: Field-aware Embedding Dimension Searchin Recommender Systems. - Xiangyu Zhao 001; Haochen Liu; Hui Liu 031; Jiliang Tang; Weiwei Guo; Jun Shi; Sida Wang 002; Huiji Gao; Bo Long (WWW, 2021)

UserSim: User Simulation via Supervised GenerativeAdversarial Network. - Xiangyu Zhao 001; Long Xia; Lixin Zou; Hui Liu 031; Dawei Yin; Jiliang Tang (WWW, 2021)

The Untold Secrets of WiFi-Calling Services: Vulnerabilities, Attacks, and Countermeasures. - Tian Xie 001; Guan-Hua Tu; Bangjie Yin; Chi-Yu Li 001; Chunyi Peng 001; Mi Zhang 002; Hui Liu 031; Xiaoming Liu 002 (IEEE Trans. Mob. Comput., 2021)

Multi-Type Urban Crime Prediction. - Xiangyu Zhao 001; Wenqi Fan; Hui Liu 031; Jiliang Tang (AAAI, 2022)

Toward Annotator Group Bias in Crowdsourcing. - Haochen Liu; Joseph Thekinen; Sinem Mollaoglu; Da Tang; Ji Yang; Youlong Cheng; Hui Liu 031; Jiliang Tang (ACL (1), 2022)

PROPN: Personalized Probabilistic Strategic Parameter Optimization in Recommendations. - Pengfei He; Haochen Liu; Xiangyu Zhao 001; Hui Liu 031; Jiliang Tang (CIKM, 2022)

Enhancing Individual Fairness through Propensity Score Matching. - Hamid Karimi; Muhammad Fawad Akbar Khan; Haochen Liu; Tyler Derr; Hui Liu 031 (DSAA, 2022)

Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. - Enyan Dai; Wei Jin 009; Hui Liu 031; Suhang Wang (WSDM, 2022)

Rating Distribution Calibration for Selection Bias Mitigation in Recommendations. - Haochen Liu; Da Tang; Ji Yang; Xiangyu Zhao 001; Hui Liu 031; Jiliang Tang; Youlong Cheng (WWW, 2022)

Learning Representations for Hyper-Relational Knowledge Graphs. - Harry Shomer; Wei Jin 009; Juanhui Li; Yao Ma 001; Hui Liu 031 (ASONAM, 2023)

A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data. - Wentao Wang 006; Harry Shomer; Yuxuan Wan; Yaxin Li 001; Jiangtao Huang; Hui Liu 031 (CIKM, 2023)

Single-Cell Multimodal Prediction via Transformers. - Wenzhuo Tang; Hongzhi Wen; Renming Liu; Jiayuan Ding; Wei Jin 009; Yuying Xie 001; Hui Liu 031; Jiliang Tang (CIKM, 2023)

Probabilistic Categorical Adversarial Attack and Adversarial Training. - Han Xu 002; Pengfei He; Jie Ren 019; Yuxuan Wan; Zitao Liu 001; Hui Liu 031; Jiliang Tang (ICML, 2023)

Generative Diffusion Models on Graphs: Methods and Applications. - Chengyi Liu; Wenqi Fan; Yunqing Liu; Jiatong Li 003; Hang Li 007; Hui Liu 031; Jiliang Tang; Qing Li 001 (IJCAI, 2023)

Enhancing Graph Representations Learning with Decorrelated Propagation. - Hua Liu; Haoyu Han 001; Wei Jin 009; Xiaorui Liu; Hui Liu 031 (KDD, 2023)

Counterfactual Learning on Graphs: A Survey. - Zhimeng Guo; Teng Xiao; Charu Aggarwal 001; Hui Liu 031; Suhang Wang (CoRR, 2023)

Self-Explainable Graph Neural Networks for Link Prediction. - Huaisheng Zhu; Dongsheng Luo; Xianfeng Tang; Junjie Xu; Hui Liu 031; Suhang Wang (CoRR, 2023)

Sharpness-Aware Data Poisoning Attack. - Pengfei He; Han Xu 002; Jie Ren 019; Yingqian Cui; Hui Liu 031; Charu C. Aggarwal; Jiliang Tang (CoRR, 2023)

DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models. - Yingqian Cui; Jie Ren 019; Han Xu 002; Pengfei He; Hui Liu 031; Lichao Sun 001; Jiliang Tang (CoRR, 2023)

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. - Yingqian Cui; Jie Ren 019; Yuping Lin; Han Xu 002; Pengfei He; Yue Xing 002; Wenqi Fan; Hui Liu 031; Jiliang Tang (CoRR, 2023)

Augment with Care: Enhancing Graph Contrastive Learning with Selective Spectrum Perturbation. - Kaiqi Yang 001; Haoyu Han 001; Wei Jin 009; Hui Liu 031 (CoRR, 2023)

Learning fair models without sensitive attributes: A generative approach. - Huaisheng Zhu; Enyan Dai; Hui Liu 031; Suhang Wang (Neurocomputing, 2023)

Exploring the Potential of Large Language Models (LLMs)in Learning on Graphs. - Zhikai Chen; Haitao Mao; Hang Li 007; Wei Jin 009; Hongzhi Wen; Xiaochi Wei; Shuaiqiang Wang; Dawei Yin; Wenqi Fan; Hui Liu 031; Jiliang Tang (SIGKDD Explor., 2023)

Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles. - Wenqi Fan; Xiangyu Zhao 001; Qing Li 001; Tyler Derr; Yao Ma 001; Hui Liu 031; Jianping Wang 001; Jiliang Tang (IEEE Trans. Knowl. Data Eng., 2023)

Content Knowledge Identification with Multi-agent Large Language Models (LLMs). - Kaiqi Yang 001; Yucheng Chu; Taylor Darwin; Ahreum Han; Hang Li 007; Hongzhi Wen; Yasemin Copur-Gencturk; Jiliang Tang; Hui Liu 031 (AIED (2), 2024)

Spectral-Aware Augmentation for Enhanced Graph Representation Learning. - Kaiqi Yang 001; Haoyu Han 001; Wei Jin 009; Hui Liu 031 (CIKM, 2024)

Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis. - Yuping Lin; Pengfei He; Han Xu 002; Yue Xing 002; Makoto Yamada; Hui Liu 031; Jiliang Tang (EMNLP, 2024)

On the Generalization of Training-based ChatGPT Detection Methods. - Han Xu 002; Jie Ren 019; Pengfei He; Shenglai Zeng; Yingqian Cui; Amy Liu; Hui Liu 031; Jiliang Tang (EMNLP (Findings), 2024)

Are Large Language Models (LLMs) Good Social Predictors? - Kaiqi Yang 001; Hang Li 007; Hongzhi Wen; Tai-Quan Peng; Jiliang Tang; Hui Liu 031 (EMNLP (Findings), 2024)

Label-free Node Classification on Graphs with Large Language Models (LLMs). - Zhikai Chen; Haitao Mao; Hongzhi Wen; Haoyu Han 001; Wei Jin 009; Haiyang Zhang; Hui Liu 031; Jiliang Tang (ICLR, 2024)

Structural Fairness-aware Active Learning for Graph Neural Networks. - Haoyu Han 001; Xiaorui Liu; Li Ma 012; MohamadAli Torkamani; Hui Liu 031; Jiliang Tang; Makoto Yamada (ICLR, 2024)

Sharpness-Aware Data Poisoning Attack. - Pengfei He; Han Xu 002; Jie Ren 019; Yingqian Cui; Shenglai Zeng; Hui Liu 031; Charu C. Aggarwal; Jiliang Tang (ICLR, 2024)

A Pure Transformer Pretraining Framework on Text-Attributed Graphs. - Yu Song; Haitao Mao; Jiachen Xiao; Jingzhe Liu; Zhikai Chen; Wei Jin 009; Carl Yang 001; Jiliang Tang; Hui Liu 031 (LoG, 2024)

Mixture of Link Predictors on Graphs. - Li Ma 012; Haoyu Han 001; Juanhui Li; Harry Shomer; Hui Liu 031; Xiaofeng Gao 001; Jiliang Tang (NeurIPS, 2024)

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. - Zhikai Chen; Haitao Mao; Jingzhe Liu; Yu Song; Bingheng Li; Wei Jin 009; Bahare Fatemi; Anton Tsitsulin; Bryan Perozzi; Hui Liu 031; Jiliang Tang (NeurIPS, 2024)

Neural Style Protection: Counteracting Unauthorized Neural Style Transfer. - Yaxin Li 001; Jie Ren 019; Han Xu 002; Hui Liu 031 (WACV, 2024)

Copyright Protection in Generative AI: A Technical Perspective. - Jie Ren 019; Han Xu 002; Pengfei He; Yingqian Cui; Shenglai Zeng; Jiankun Zhang; Hongzhi Wen; Jiayuan Ding; Hui Liu 031; Yi Chang 001; Jiliang Tang (CoRR, 2024)

Mixture of Link Predictors. - Li Ma 012; Haoyu Han 001; Juanhui Li; Harry Shomer; Hui Liu 031; Xiaofeng Gao 001; Jiliang Tang (CoRR, 2024)

Rethinking Large Language Model Architectures for Sequential Recommendations. - Hanbing Wang; Xiaorui Liu; Wenqi Fan; Xiangyu Zhao 001; Venkataramana Kini; Devendra Yadav; Fei Wang; Zhen Wen; Jiliang Tang; Hui Liu 031 (CoRR, 2024)

Graph Machine Learning in the Era of Large Language Models (LLMs). - Wenqi Fan; Shijie Wang 002; Jiani Huang 001; Zhikai Chen; Yu Song; Wenzhuo Tang; Haitao Mao; Hui Liu 031; Xiaorui Liu; Dawei Yin; Qing Li 001 (CoRR, 2024)

Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data. - Shenglai Zeng; Jiankun Zhang; Pengfei He; Jie Ren 019; Tianqi Zheng; Hanqing Lu; Han Xu 002; Hui Liu 031; Yue Xing 002; Jiliang Tang (CoRR, 2024)

Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models. - Jie Ren 019; Kangrui Chen; Yingqian Cui; Shenglai Zeng; Hui Liu 031; Yue Xing 002; Jiliang Tang; Lingjuan Lyu (CoRR, 2024)

A Survey of Mamba. - Haohao Qu; Liangbo Ning 001; Rui An; Wenqi Fan; Tyler Derr; Hui Liu 031; Xin Xu 002; Qing Li 001 (CoRR, 2024)

A LLM-Powered Automatic Grading Framework with Human-Level Guidelines Optimization. - Yucheng Chu; Hang Li 007; Kaiqi Yang 001; Harry Shomer; Hui Liu 031; Yasemin Copur-Gencturk; Jiliang Tang (CoRR, 2024)

Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study. - Pengfei He; Yingqian Cui; Han Xu 002; Hui Liu 031; Makoto Yamada; Jiliang Tang; Yue Xing 002 (CoRR, 2024)

Divide-Verify-Refine: Aligning LLM Responses with Complex Instructions. - Xianren Zhang; Xianfeng Tang; Hui Liu 031; Zongyu Wu 001; Qi He 002; Dongwon Lee 001; Suhang Wang (CoRR, 2024)

Exploring Social Desirability Response Bias in Large Language Models: Evidence from GPT-4 Simulations. - Sanguk Lee; Kaiqi Yang 001; Tai-Quan Peng; Ruth Heo; Hui Liu 031 (CoRR, 2024)

Does your LLM truly unlearn? An embarrassingly simple approach to recover unlearned knowledge. - Zhiwei Zhang; Fali Wang; Xiaomin Li; Zongyu Wu 001; Xianfeng Tang; Hui Liu 031; Qi He 002; Wenpeng Yin 001; Suhang Wang (CoRR, 2024)

Unpacking Political Bias in Large Language Models: Insights Across Topic Polarization. - Kaiqi Yang 001; Hang Li 007; Yucheng Chu; Yuping Lin; Tai-Quan Peng; Hui Liu 031 (CoRR, 2024)

Empowering Molecule Discovery for Molecule-Caption Translation With Large Language Models: A ChatGPT Perspective. - Jiatong Li 003; Yunqing Liu; Wenqi Fan; Xiao-Yong Wei; Hui Liu 031; Jiliang Tang; Qing Li 001 (IEEE Trans. Knowl. Data Eng., 2024)

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. - Enyan Dai; Tianxiang Zhao 001; Huaisheng Zhu; Junjie Xu; Zhimeng Guo; Hui Liu 031; Jiliang Tang; Suhang Wang (Mach. Intell. Res., 2024)

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. - Yingqian Cui; Jie Ren 019; Yuping Lin; Han Xu 002; Pengfei He; Yue Xing 002; Lingjuan Lyu; Wenqi Fan; Hui Liu 031; Jiliang Tang (SIGKDD Explor., 2024)

DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models. - Yingqian Cui; Jie Ren 019; Han Xu 002; Pengfei He; Hui Liu 031; Lichao Sun 001; Yue Xing 002; Jiliang Tang (SIGKDD Explor., 2024)

Ask-Before-Detection: Identifying and Mitigating Conformity Bias in LLM-Powered Error Detector for Math Word Problem Solutions. - Hang Li 007; Tianlong Xu; Kaiqi Yang 001; Yucheng Chu; Yanling Chen; Yichi Song; Qingsong Wen; Hui Liu 031 (ACL (1), 2025)

Red-Teaming LLM Multi-Agent Systems via Communication Attacks. - Pengfei He; Yuping Lin; Shen Dong; Han Xu 002; Yue Xing 002; Hui Liu 031 (ACL (Findings), 2025)

Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach. - Shenglai Zeng; Pengfei He; Kai Guo 003; Tianqi Zheng; Hanqing Lu; Yue Xing 002; Hui Liu 031 (ACL (1), 2025)

Divide-Verify-Refine: Can LLMs Self-align with Complex Instructions? - Xianren Zhang; Xianfeng Tang; Hui Liu 031; Zongyu Wu 001; Qi He 002; Dongwon Lee 001; Suhang Wang (ACL (Findings), 2025)

Superiority of Multi-Head Attention: A Theoretical Study in Shallow Transformers in In-Context Linear Regression. - Yingqian Cui; Jie Ren 019; Pengfei He; Hui Liu 031; Jiliang Tang; Yue Xing 002 (AISTATS, 2025)

A LLM-Powered Automatic Grading Framework with Human-Level Guidelines Optimization. - Yucheng Chu; Hang Li 007; Kaiqi Yang 001; Harry Shomer; Yasemin Copur-Gencturk; Leonora Kaldaras; Kevin C. Haudek; Joseph Krajcik; Namsoo Shin; Hui Liu 031; Jiliang Tang (EDM, 2025)

Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning. - Tianci Liu 003; Ruirui Li 002; Yunzhe Qi; Hui Liu 031; Xianfeng Tang; Tianqi Zheng; Qingyu Yin; Monica Xiao Cheng; Jun Huan; Haoyu Wang 004; Jing Gao 004 (ICLR, 2025)

Catastrophic Failure of LLM Unlearning via Quantization. - Zhiwei Zhang; Fali Wang; Xiaomin Li; Zongyu Wu 001; Xianfeng Tang; Hui Liu 031; Qi He 002; Wenpeng Yin 001; Suhang Wang (ICLR, 2025)

Data Poisoning for In-context Learning. - Pengfei He; Han Xu 002; Yue Xing 002; Hui Liu 031; Makoto Yamada; Jiliang Tang (NAACL (Findings), 2025)

Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data. - Juanhui Li; Sreyashi Nag; Hui Liu 031; Xianfeng Tang; Sheikh Muhammad Sarwar; Limeng Cui; Hansu Gu; Suhang Wang; Qi He 002; Jiliang Tang (NAACL (Findings), 2025)

SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains. - Ran Xu 002; Hui Liu 031; Sreyashi Nag; Zhenwei Dai; Yaochen Xie; Xianfeng Tang; Chen Luo 003; Yang Li 055; Joyce C. Ho; Carl Yang 001; Qi He 002 (NAACL (Long Papers), 2025)

Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective. - Shenglai Zeng; Jiankun Zhang; Bingheng Li; Yuping Lin; Tianqi Zheng; Dante Everaert; Hanqing Lu; Hui Liu 031; Yue Xing 002; Monica Xiao Cheng; Jiliang Tang (NAACL (Long Papers), 2025)

Computational Protein Science in the Era of Large Language Models (LLMs). - Wenqi Fan; Yi Zhou; Shijie Wang 002; Yuyao Yan; Hui Liu 031; Qian Zhao; Le Song; Qing Li 001 (CoRR, 2025)

RAG vs. GraphRAG: A Systematic Evaluation and Key Insights. - Haoyu Han 001; Harry Shomer; Yu Wang 160; Yongjia Lei; Kai Guo 003; Zhigang Hua; Bo Long; Hui Liu 031; Jiliang Tang (CoRR, 2025)

Red-Teaming LLM Multi-Agent Systems via Communication Attacks. - Pengfei He; Yupin Lin; Shen Dong; Han Xu 002; Yue Xing 002; Hui Liu 031 (CoRR, 2025)

Counterfactual Learning on Graphs: A Survey. - Zhimeng Guo; Zongyu Wu 001; Teng Xiao; Charu Aggarwal 001; Hui Liu 031; Suhang Wang (Mach. Intell. Res., 2025)

A Practical Memory Injection Attack against LLM Agents. - Shen Dong; Shaochen Xu; Pengfei He; Yige Li; Jiliang Tang; Tianming Liu 001; Hui Liu 031; Zhen Xiang (CoRR, 2025)

ViLBench: A Suite for Vision-Language Process Reward Modeling. - Haoqin Tu; Weitao Feng; Hardy Chen; Hui Liu 031; Xianfeng Tang; Cihang Xie (CoRR, 2025)

A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Models. - Liangbo Ning 001; Ziran Liang; Zhuohang Jiang; Haohao Qu; Yujuan Ding; Wenqi Fan; Xiaoyong Wei; Shanru Lin; Hui Liu 031; Philip S. Yu; Qing Li 001 (CoRR, 2025)

m1: Unleash the Potential of Test-Time Scaling for Medical Reasoning with Large Language Models. - Xiaoke Huang; Juncheng Wu; Hui Liu 031; Xianfeng Tang; Yuyin Zhou (CoRR, 2025)

SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models. - Hardy Chen; Haoqin Tu; Fali Wang; Hui Liu 031; Xianfeng Tang; Xinya Du; Yuyin Zhou; Cihang Xie (CoRR, 2025)

Beyond Text: Unveiling Privacy Vulnerabilities in Multi-modal Retrieval-Augmented Generation. - Jiankun Zhang; Shenglai Zeng; Jie Ren 019; Tianqi Zheng; Hui Liu 031; Xianfeng Tang; Hui Liu 031; Yi Chang 001 (CoRR, 2025)

Beyond Text: Unveiling Privacy Vulnerabilities in Multi-modal Retrieval-Augmented Generation. - Jiankun Zhang; Shenglai Zeng; Jie Ren 019; Tianqi Zheng; Hui Liu 031; Xianfeng Tang; Hui Liu 031; Yi Chang 001 (CoRR, 2025)

Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy. - Jie Ren 019; Zhenwei Dai; Xianfeng Tang; Yue Xing 002; Shenglai Zeng; Hui Liu 031; Jingying Zeng; Qiankun Peng; Samarth Varshney; Suhang Wang; Qi He 002; Charu C. Aggarwal; et al. (CoRR, 2025)

Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy. - Jie Ren 019; Zhenwei Dai; Xianfeng Tang; Yue Xing 002; Shenglai Zeng; Hui Liu 031; Jingying Zeng; Qiankun Peng; Samarth Varshney; Suhang Wang; Qi He 002; Charu C. Aggarwal; et al. (CoRR, 2025)

Comprehensive Vulnerability Analysis is Necessary for Trustworthy LLM-MAS. - Pengfei He; Yue Xing 002; Shen Dong; Juanhui Li; Zhenwei Dai; Xianfeng Tang; Hui Liu 031; Han Xu 002; Zhen Xiang; Charu C. Aggarwal; Hui Liu 031 (CoRR, 2025)

Comprehensive Vulnerability Analysis is Necessary for Trustworthy LLM-MAS. - Pengfei He; Yue Xing 002; Shen Dong; Juanhui Li; Zhenwei Dai; Xianfeng Tang; Hui Liu 031; Han Xu 002; Zhen Xiang; Charu C. Aggarwal; Hui Liu 031 (CoRR, 2025)

SoK: Machine Unlearning for Large Language Models. - Jie Ren 019; Yue Xing 002; Yingqian Cui; Charu C. Aggarwal; Hui Liu 031 (CoRR, 2025)

Does Multimodal Large Language Model Truly Unlearn? Stealthy MLLM Unlearning Attack. - Xianren Zhang; Hui Liu 031; Delvin Ce Zhang; Xianfeng Tang; Qi He 002; Dongwon Lee 001; Suhang Wang (CoRR, 2025)

A LLM-Driven Multi-Agent Systems for Professional Development of Mathematics Teachers. - Kaiqi Yang 001; Hang Li 007; Yucheng Chu; Ahreum Han; Yasemin Copur-Gencturk; Jiliang Tang; Hui Liu 031 (CoRR, 2025)

AgentTTS: Large Language Model Agent for Test-time Compute-optimal Scaling Strategy in Complex Tasks. - Fali Wang; Hui Liu 031; Zhenwei Dai; Jingying Zeng; Zhiwei Zhang; Zongyu Wu 001; Chen Luo 003; Zheng Li 018; Xianfeng Tang; Qi He 002; Suhang Wang (CoRR, 2025)

MedVLThinker: Simple Baselines for Multimodal Medical Reasoning. - Xiaoke Huang; Juncheng Wu; Hui Liu 031; Xianfeng Tang; Yuyin Zhou (CoRR, 2025)

A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation. - Yu Song; Zhigang Hua; Harry Shomer; Yan Xie; Jingzhe Liu; Bo Long; Hui Liu 031 (CoRR, 2025)