Liu, Yixin

26 publications

AAAI 2025 A Label-Free Heterophily-Guided Approach for Unsupervised Graph Fraud Detection Junjun Pan, Yixin Liu, Xin Zheng, Yizhen Zheng, Alan Wee-Chung Liew, Fuyi Li, Shirui Pan

AAAI 2025 Evaluating Mathematical Reasoning Beyond Accuracy Shijie Xia, Xuefeng Li, Yixin Liu, Tongshuang Wu, Pengfei Liu

CVPR 2025 MMVU: Measuring Expert-Level Multi-Discipline Video Understanding Yilun Zhao, Haowei Zhang, Lujing Xie, Tongyan Hu, Guo Gan, Yitao Long, Zhiyuan Hu, Weiyuan Chen, Chuhan Li, Zhijian Xu, Chengye Wang, Ziyao Shangguan, Zhenwen Liang, Yixin Liu, Chen Zhao, Arman Cohan

NeurIPS 2025 On Evaluating LLM Alignment by Evaluating LLMs as Judges Yixin Liu, Pengfei Liu, Arman Cohan

ICLRW 2025 PHYSICS: Benchmarking Foundation Models for Problem Solving in Physics Kaiyue Feng, Yilun Zhao, Yixin Liu, Tianyu Yang, Chen Zhao, John Sous, Arman Cohan

NeurIPS 2025 RTV-Bench: Benchmarking MLLM Continuous Perception, Understanding and Reasoning Through Real-Time Video ShuHang Xun, Sicheng Tao, Jungang Li, Yibo Shi, Zhixin Lin, Zhanhui Zhu, Yibo Yan, Hanqian Li, LingHao Zhang, Shikang Wang, Yixin Liu, Hanbo Zhang, Ying Ma, Xuming Hu

NeurIPS 2025 SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks Yilun Zhao, Kaiyan Zhang, Tiansheng Hu, Sihong Wu, Ronan Le Bras, Yixin Liu, Xiangru Tang, Joseph Chee Chang, Jesse Dodge, Jonathan Bragg, Chen Zhao, Hannaneh Hajishirzi, Doug Downey, Arman Cohan

ICLR 2025 Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark Yili Wang, Yixin Liu, Xu Shen, Chenyu Li, Rui Miao, Kaize Ding, Ying Wang, Shirui Pan, Xin Wang

ICML 2025 XAttnMark: Learning Robust Audio Watermarking with Cross-Attention Yixin Liu, Lie Lu, Jihui Jin, Lichao Sun, Andrea Fanelli

NeurIPS 2024 ARC: A Generalist Graph Anomaly Detector with In-Context Learning Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, Shirui Pan

NeurIPSW 2024 COMAL: A Convergent Meta-Algorithm for Aligning LLMs with General Preferences Yixin Liu, Argyris Oikonomou, Weiqiang Zheng, Yang Cai, Arman Cohan

ECCV 2024 EditShield: Protecting Unauthorized Image Editing by Instruction-Guided Diffusion Models Ruoxi Chen, Haibo Jin, Yixin Liu, Jinyin Chen, Haohan Wang, Lichao Sun

AAAI 2024 GOODAT: Towards Test-Time Graph Out-of-Distribution Detection Luzhi Wang, Dongxiao He, He Zhang, Yixin Liu, Wenjie Wang, Shirui Pan, Di Jin, Tat-Seng Chua

NeurIPSW 2024 Hetero-UNet: Heterogeneous Transformer with Mamba for Medical Image Segmentation Zhiling Yan, Yixin Liu, Xiang Li, Lichao Sun

ICML 2024 Improving Interpretation Faithfulness for Vision Transformers Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang

ICMLW 2024 Medical Unlearnable Examples: Securing Medical Data from Unauthorized Training via Sparsity-Aware Local Masking Weixiang Sun, Yixin Liu, Zhiling Yan, Kaidi Xu, Lichao Sun

CVPR 2024 MetaCloak: Preventing Unauthorized Subject-Driven Text-to-Image Diffusion-Based Synthesis via Meta-Learning Yixin Liu, Chenrui Fan, Yutong Dai, Xun Chen, Pan Zhou, Lichao Sun

ICLR 2024 MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use Yue Huang, Jiawen Shi, Yuan Li, Chenrui Fan, Siyuan Wu, Qihui Zhang, Yixin Liu, Pan Zhou, Yao Wan, Neil Zhenqiang Gong, Lichao Sun

ICML 2024 Position: TrustLLM: Trustworthiness in Large Language Models Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Yang Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao

NeurIPSW 2024 SCIURus: Shared Circuits for Interpretable Uncertainty Representations in Language Models Carter Teplica, Yixin Liu, Arman Cohan, Tim G. J. Rudner

NeurIPSW 2024 SCIURus: Shared Circuits for Interpretable Uncertainty Representations in Language Models Carter Teplica, Yixin Liu, Arman Cohan, Tim G. J. Rudner

AAAI 2024 Stable Unlearnable Example: Enhancing the Robustness of Unlearnable Examples via Stable Error-Minimizing Noise Yixin Liu, Kaidi Xu, Xun Chen, Lichao Sun

AAAI 2023 Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating Yixin Liu, Yizhen Zheng, Daokun Zhang, Vincent C. S. Lee, Shirui Pan

AAAI 2023 Federated Learning on Non-IID Graphs via Structural Knowledge Sharing Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang

AAAI 2023 SEAT: Stable and Explainable Attention Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang

NeurIPS 2023 Towards Self-Interpretable Graph-Level Anomaly Detection Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan