BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs. - Kay Liu; Yingtong Dou; Yue Zhao 016; Xueying Ding; Xiyang Hu; Ruitong Zhang; Kaize Ding; Canyu Chen; Hao Peng 001; Kai Shu; Lichao Sun 001; Jundong Li; et al. (NeurIPS, 2022)

Artificial Intelligence Algorithms for Treatment of Diabetes. - Mudassir M. Rashid; Mohammad-Reza Askari; Canyu Chen; Yueqing Liang; Kai Shu; Ali Cinar (Algorithms, 2022)

PyGOD: A Python Library for Graph Outlier Detection. - Kay Liu; Yingtong Dou; Yue Zhao 016; Xueying Ding; Xiyang Hu; Ruitong Zhang; Kaize Ding; Canyu Chen; Hao Peng 001; Kai Shu; George H. Chen; Zhihao Jia; et al. (CoRR, 2022)

Joint Adversarial Learning for Cross-domain Fair Classification. - Yueqing Liang; Canyu Chen; Tian Tian; Kai Shu (CoRR, 2022)

Benchmarking Node Outlier Detection on Graphs. - Kay Liu; Yingtong Dou; Yue Zhao 016; Xueying Ding; Xiyang Hu; Ruitong Zhang; Kaize Ding; Canyu Chen; Hao Peng 001; Kai Shu; Lichao Sun 001; Jundong Li; et al. (CoRR, 2022)

On Fair Classification with Mostly Private Sensitive Attributes. - Canyu Chen; Yueqing Liang; Xiongxiao Xu; Shangyu Xie; Yuan Hong 001; Kai Shu (CoRR, 2022)

Combating Health Misinformation in Social Media: Characterization, Detection, Intervention, and Open Issues. - Canyu Chen; Haoran Wang 005; Matthew Shapiro; Yunyu Xiao; Fei Wang; Kai Shu (CoRR, 2022)

Fair classification via domain adaptation: A dual adversarial learning approach. - Yueqing Liang; Canyu Chen; Tian Tian; Kai Shu (Frontiers Big Data, 2022)

PromptDA: Label-guided Data Augmentation for Prompt-based Few Shot Learners. - Canyu Chen; Kai Shu (EACL, 2023)

Attacking Fake News Detectors via Manipulating News Social Engagement. - Haoran Wang 005; Yingtong Dou; Canyu Chen; Lichao Sun 001; Philip S. Yu; Kai Shu (WWW, 2023)

MetaGAD: Learning to Meta Transfer for Few-shot Graph Anomaly Detection. - Xiongxiao Xu; Kaize Ding; Canyu Chen; Kai Shu (CoRR, 2023)

Model Attribution in LLM-Generated Disinformation: A Domain Generalization Approach with Supervised Contrastive Learning. - Alimohammad Beigi; Zhen Tan 001; Nivedh Mudiam; Canyu Chen; Kai Shu; Huan Liu 001 (DSAA, 2024)

MetaGAD: Meta Representation Adaptation for Few-Shot Graph Anomaly Detection. - Xiongxiao Xu; Kaize Ding; Canyu Chen; Kai Shu (DSAA, 2024)

Can Large Language Models Identify Authorship? - Baixiang Huang; Canyu Chen; Kai Shu (EMNLP (Findings), 2024)

Can LLM-Generated Misinformation Be Detected? - Canyu Chen; Kai Shu (ICLR, 2024)

Can Large Language Model Agents Simulate Human Trust Behavior? - Chengxing Xie; Canyu Chen; Feiran Jia; Ziyu Ye; Shiyang Lai; Kai Shu; Jindong Gu; Adel Bibi; Ziniu Hu; David Jurgens; James Evans; Philip Torr 001; et al. (NeurIPS, 2024)

Combating misinformation in the age of LLMs: Opportunities and challenges. - Canyu Chen; Kai Shu (AI Mag., 2024)

Can Large Language Model Agents Simulate Human Trust Behaviors? - Chengxing Xie; Canyu Chen; Feiran Jia; Ziyu Ye; Kai Shu; Adel Bibi; Ziniu Hu; Philip Torr 001; Bernard Ghanem; Guohao Li 001 (CoRR, 2024)

Introducing v0.5 of the AI Safety Benchmark from MLCommons. - Bertie Vidgen; Adarsh Agrawal; Ahmed M. Ahmed 004; Victor Akinwande; Namir Al-Nuaimi; Najla Alfaraj; Elie Alhajjar; Lora Aroyo; Trupti Bavalatti; Borhane Blili-Hamelin; Kurt D. Bollacker; Rishi Bomassani; et al. (CoRR, 2024)

MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation? - Zhaorun Chen; Yichao Du; Zichen Wen; Yiyang Zhou; Chenhang Cui; Zhenzhen Weng; Haoqin Tu; Chaoqi Wang; Zhengwei Tong; Qinglan Huang; Canyu Chen; Qinghao Ye; et al. (CoRR, 2024)

Can Editing LLMs Inject Harm? - Canyu Chen; Baixiang Huang; Zekun Li 008; Zhaorun Chen; Shiyang Lai; Xiongxiao Xu; Jia-Chen Gu; Jindong Gu; Huaxiu Yao; Chaowei Xiao; Xifeng Yan; William Yang Wang; et al. (CoRR, 2024)

Model Attribution in Machine-Generated Disinformation: A Domain Generalization Approach with Supervised Contrastive Learning. - Alimohammad Beigi; Zhen Tan 001; Nivedh Mudiam; Canyu Chen; Kai Shu; Huan Liu 001 (CoRR, 2024)

FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks. - Peiran Wu; Che Liu; Canyu Chen; Jun Li; Cosmin I. Bercea; Rossella Arcucci (CoRR, 2024)

FairMindSim: Alignment of Behavior, Emotion, and Belief in Humans and LLM Agents Amid Ethical Dilemmas. - Yu Lei; Hao Liu; Chengxing Xie; Songjia Liu; Zhiyu Yin; Canyu Chen; Guohao Li 013; Philip Torr 001; Zhen Wu (CoRR, 2024)

ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction? - Canyu Chen; Jian Yu; Shan Chen 004; Che Liu; Zhongwei Wan; Danielle S. Bitterman; Fei Wang; Kai Shu (CoRR, 2024)

From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge. - Dawei Li 008; Bohan Jiang; Liangjie Huang; Alimohammad Beigi; Chengshuai Zhao; Zhen Tan 001; Amrita Bhattacharjee; Yuxuan Jiang; Canyu Chen; Tianhao Wu; Kai Shu; Lu Cheng 001; et al. (CoRR, 2024)

Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges. - Baixiang Huang; Canyu Chen; Kai Shu (SIGKDD Explor., 2024)

Can Knowledge Editing Really Correct Hallucinations? - Baixiang Huang; Canyu Chen; Xiongxiao Xu; Ali Payani; Kai Shu (ICLR, 2025)

Wetland Scene Segmentation of Remote Sensing Images Based on Lie Group Feature and Graph Cut Model. - Canyu Chen; Guobin Zhu; Xiliang Chen (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)

SearchRAG: Can Search Engines Be Helpful for LLM-based Medical Question Answering? - Yucheng Shi; Tianze Yang; Canyu Chen; Quanzheng Li; Tianming Liu 001; Xiang Li 001; Ninghao Liu (CoRR, 2025)

AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons. - Shaona Ghosh; Heather Frase; Adina Williams; Sarah Luger; Paul Röttger; Fazl Barez; Sean McGregor; Kenneth Fricklas; Mala Kumar; Quentin Feuillade-Montixi; Kurt Bollacker; Felix Friedrich; et al. (CoRR, 2025)

Chameleon: On the Scene Diversity and Domain Variety of AI-Generated Videos Detection. - Meiyu Zeng; Xingming Liao; Canyu Chen; Nankai Lin; Zhuowei Wang 001; Chong Chen 010; Aimin Yang 002 (CoRR, 2025)