Chen, Yuhan

16 publications

ICLR 2025 Decoupled Graph Energy-Based Model for Node Out-of-Distribution Detection on Heterophilic Graphs Yuhan Chen, Yihong Luo, Yifan Song, Pengwen Dai, Jing Tang, Xiaochun Cao

AAAI 2025 Investigating the Security Threat Arising from "Yes-No" Implicit Bias in Large Language Models Yanrui Du, Sendong Zhao, Ming Ma, Yuhan Chen, Bing Qin

ICLR 2025 STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs Peijie Dong, Lujun Li, Yuedong Zhong, DaYou Du, Ruibo Fan, Yuhan Chen, Zhenheng Tang, Qiang Wang, Wei Xue, Yike Guo, Xiaowen Chu

NeurIPS 2024 CausalChaos! Dataset for Comprehensive Causal Action Question Answering over Longer Causal Chains Grounded in Dynamic Visual Scenes Paritosh Parmar, Eric Peh, Ruirui Chen, Ting En Lam, Yuhan Chen, Elston Tan, Basura Fernando

NeurIPS 2024 Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification Yihong Luo, Yuhan Chen, Siya Qiu, Yiwei Wang, Chen Zhang, Yan Zhou, Xiaochun Cao, Jing Tang

AAAI 2024 From Artificially Real to Real: Leveraging Pseudo Data from Large Language Models for Low-Resource Molecule Discovery Yuhan Chen, Nuwa Xi, Yanrui Du, Haochun Wang, Jianyu Chen, Sendong Zhao, Bing Qin

NeurIPS 2024 Mixture of In-Context Experts Enhance LLMs' Long Context Awareness Hongzhan Lin, Ang Lv, Yuhan Chen, Chen Zhu, Yang Song, Hengshu Zhu, Rui Yan

NeurIPS 2024 MoGU: A Framework for Enhancing Safety of LLMs While Preserving Their Usability Yanrui Du, Sendong Zhao, Danyang Zhao, Ming Ma, Yuhan Chen, Liangyu Huo, Qing Yang, Dongliang Xu, Bing Qin

JMLR 2024 PirateNets: Physics-Informed Deep Learning with Residual Adaptive Networks Sifan Wang, Bowen Li, Yuhan Chen, Paris Perdikaris

ICMLW 2023 Equivalence Class Learning for GENERIC Systems Baige Xu, Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi

IJCAI 2023 LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao

AAAI 2023 PEN: Prediction-Explanation Network to Forecast Stock Price Movement with Better Explainability Shuqi Li, Weiheng Liao, Yuhan Chen, Rui Yan

ICMLW 2023 Variational Principle and Variational Integrators for Neural Symplectic Forms Yuhan Chen, Baige Xu, Takashi Matsubara, Takaharu Yaguchi

NeurIPS 2022 Debiased, Longitudinal and Coordinated Drug Recommendation Through Multi-Visit Clinic Records Hongda Sun, Shufang Xie, Shuqi Li, Yuhan Chen, Ji-Rong Wen, Rui Yan

AAAI 2022 KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-Zero Training Loss Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi

NeurIPS 2021 Neural Symplectic Form: Learning Hamiltonian Equations on General Coordinate Systems Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi