Informative Visual Storytelling with Cross-modal Rules. - Jiacheng Li 002; Haizhou Shi; Siliang Tang; Fei Wu 001; Yueting Zhuang (ACM Multimedia, 2019)

Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation. - Juncheng Li 006; Xin Wang 061; Siliang Tang; Haizhou Shi; Fei Wu 001; Yueting Zhuang; William Yang Wang (CVPR, 2020)

Relational Graph Learning for Grounded Video Description Generation. - Wenqiao Zhang; Xin Eric Wang; Siliang Tang; Haizhou Shi; Haochen Shi; Jun Xiao 001; Yueting Zhuang; William Yang Wang (ACM Multimedia, 2020)

Run Away From your Teacher: Understanding BYOL by a Novel Self-Supervised Approach. - Haizhou Shi; Dongliang Luo; Siliang Tang; Jian Wang; Yueting Zhuang (CoRR, 2020)

CIL: Contrastive Instance Learning Framework for Distantly Supervised Relation Extraction. - Tao Chen; Haizhou Shi; Siliang Tang; Zhigang Chen 003; Fei Wu 001; Yueting Zhuang (ACL/IJCNLP (1), 2021)

Alleviate Representation Overlapping in Class Incremental Learning by Contrastive Class Concentration. - Zixuan Ni; Haizhou Shi; Siliang Tang; Yueting Zhuang (CoRR, 2021)

Federated Self-Supervised Contrastive Learning via Ensemble Similarity Distillation. - Haizhou Shi; Youcai Zhang; Zijin Shen; Siliang Tang; Yaqian Li; Yandong Guo; Yueting Zhuang (CoRR, 2021)

On the Efficacy of Small Self-Supervised Contrastive Models without Distillation Signals. - Haizhou Shi; Youcai Zhang; Siliang Tang; Wenjie Zhu 003; Yaqian Li; Yandong Guo; Yueting Zhuang (AAAI, 2022)

Structure-Aware Group Discrimination with Adaptive-View Graph Encoder: A Fast Graph Contrastive Learning Framework. - Zhenshuo Zhang; Yun Zhu; Haizhou Shi; Siliang Tang (ECAI, 2023)

A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm. - Haizhou Shi; Hao Wang 014 (NeurIPS, 2023)

Efficient Tuning and Inference for Large Language Models on Textual Graphs. - Yun Zhu; Yaoke Wang; Haizhou Shi; Siliang Tang (IJCAI, 2024)

BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models. - Yibin Wang 005; Haizhou Shi; Ligong Han; Dimitris N. Metaxas; Hao Wang 014 (NeurIPS, 2024)

MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning. - Yun Zhu; Haizhou Shi; Zhenshuo Zhang; Siliang Tang (WWW, 2024)

GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfer Learning. - Yun Zhu; Yaoke Wang; Haizhou Shi; Zhenshuo Zhang; Dian Jiao; Siliang Tang (WWW, 2024)

Continual Learning of Large Language Models: A Comprehensive Survey. - Haizhou Shi; Zihao Xu 001; Hengyi Wang; Weiyi Qin; Wenyuan Wang; Yibin Wang 005; Hao Wang 014 (CoRR, 2024)

UniGAP: A Universal and Adaptive Graph Upsampling Approach to Mitigate Over-Smoothing in Node Classification Tasks. - Xiaotang Wang; Yun Zhu; Haizhou Shi; Yongchao Liu; Chuntao Hong (CoRR, 2024)

Graph Triple Attention Network: A Decoupled Perspective. - Xiaotang Wang; Yun Zhu; Haizhou Shi; Yongchao Liu; Chuntao Hong (CoRR, 2024)

Graph Retrieval-Augmented Generation: A Survey. - Boci Peng; Yun Zhu; Yongchao Liu; Xiaohe Bo; Haizhou Shi; Chuntao Hong; Yan Zhang; Siliang Tang (CoRR, 2024)

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models. - Haizhou Shi; Yibin Wang 005; Ligong Han; Huan Zhang; Hao Wang 014 (CoRR, 2024)

Rate-My-LoRA: EFFICIENT AND ADAPTIVE FEDERATED MODEL TUNING FOR CARDIAC MRI SEGMENTATION. - Xiaoxiao He; Haizhou Shi; Ligong Han; Chaowei Tan; Bo Liu 005; Zihao Xu 001; Meng Ye 003; Leon Axel; Kang Li 004; Dimitris N. Metaxas (ISBI, 2025)

Graph Triple Attention Networks: A Decoupled Perspective. - Xiaotang Wang; Yun Zhu; Haizhou Shi; Yongchao Liu; Chuntao Hong (KDD (1), 2025)

Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models. - Hengyi Wang; Haizhou Shi; Shiwei Tan; Weiyi Qin; Wenyuan Wang; Tunyu Zhang; Akshay Nambi 001; Tanuja Ganu; Hao Wang 014 (NAACL (Long Papers), 2025)

GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs. - Yun Zhu; Haizhou Shi; Xiaotang Wang; Yongchao Liu; Yaoke Wang; Boci Peng; Chuntao Hong; Siliang Tang (WWW, 2025)

The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models via Visual Information Steering. - Zhuowei Li 002; Haizhou Shi; Yunhe Gao; Di Liu 003; Zhenting Wang; Yuxiao Chen 002; Ting Liu 005; Long Zhao 003; Hao Wang 014; Dimitris N. Metaxas (CoRR, 2025)

Efficient Uncertainty Estimation via Distillation of Bayesian Large Language Models. - Harshil Vejendla; Haizhou Shi; Yibin Wang; Tunyu Zhang; Huan Zhang; Hao Wang (CoRR, 2025)

Token-Level Uncertainty Estimation for Large Language Model Reasoning. - Tunyu Zhang; Haizhou Shi; Yibin Wang 005; Hengyi Wang; Xiaoxiao He; Zhuowei Li 002; Haoxian Chen 005; Ligong Han; Kai Xu; Huan Zhang; Dimitris N. Metaxas; Hao Wang 014 (CoRR, 2025)