Huang, Kexin

27 publications

ICML 2025 Automated Hypothesis Validation with Agentic Sequential Falsifications Kexin Huang, Ying Jin, Ryan Li, Michael Y. Li, Emmanuel Candes, Jure Leskovec

ICLR 2025 BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Yusuf H Roohani, Andrew H. Lee, Qian Huang, Jian Vora, Zachary Steinhart, Kexin Huang, Alexander Marson, Percy Liang, Jure Leskovec

ICML 2025 Larger or Smaller Reward Margins to Select Preferences for LLM Alignment? Kexin Huang, Junkang Wu, Ziqian Chen, Xue Wang, Jinyang Gao, Bolin Ding, Jiancan Wu, Xiangnan He, Xiang Wang

ICML 2025 Learning Bayesian Nash Equilibrium in Auction Games via Approximate Best Response Kexin Huang, Ziqian Chen, Xue Wang, Chongming Gao, Jinyang Gao, Bolin Ding, Xiang Wang

NeurIPS 2025 RePO: Understanding Preference Learning Through ReLU-Based Optimization Junkang Wu, Kexin Huang, Xue Wang, Jinyang Gao, Bolin Ding, Jiancan Wu, Xiangnan He, Xiang Wang

ICLR 2025 Toward Generalizing Visual Brain Decoding to Unseen Subjects Xiangtao Kong, Kexin Huang, Ping Li, Lei Zhang

ICML 2024 Auctionformer: A Unified Deep Learning Algorithm for Solving Equilibrium Strategies in Auction Games Kexin Huang, Ziqian Chen, Xue Wang, Chongming Gao, Jinyang Gao, Bolin Ding, Xiang Wang

NeurIPS 2024 AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning Shirley Wu, Shiyu Zhao, Qian Huang, Kexin Huang, Michihiro Yasunaga, Kaidi Cao, Vassilis N. Ioannidis, Karthik Subbian, Jure Leskovec, James Zou

NeurIPS 2024 MLLMGuard: A Multi-Dimensional Safety Evaluation Suite for Multimodal Large Language Models Tianle Gu, Zeyang Zhou, Kexin Huang, Dandan Liang, Yixu Wang, Haiquan Zhao, Yuanqi Yao, Xingge Qiao, Keqing Wang, Yujiu Yang, Yan Teng, Yu Qiao, Yingchun Wang

ICLR 2024 On the Analysis of GAN-Based Image-to-Image Translation with Gaussian Noise Injection Chaohua Shi, Kexin Huang, Lu Gan, Hongqing Liu, Mingrui Zhu, Nannan Wang, Xinbo Gao

ICML 2024 Position: Relational Deep Learning - Graph Representation Learning on Relational Databases Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec

NeurIPS 2024 RelBench: A Benchmark for Deep Learning on Relational Databases Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan E. Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec

NeurIPSW 2024 Relational Deep Learning: Graph Representation Learning on Relational Databases Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec

NeurIPS 2024 STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases Shirley Wu, Shiyu Zhao, Michihiro Yasunaga, Kexin Huang, Kaidi Cao, Qian Huang, Vassilis N. Ioannidis, Karthik Subbian, James Zou, Jure Leskovec

NeurIPSW 2024 Signals in the Cells: Multimodal and Contextualized Machine Learning Foundations for Therapeutics Alejandro Velez-Arce, Kexin Huang, Michelle M Li, Xiang Lin, Wenhao Gao, Bradley Pentelute, Tianfan Fu, Manolis Kellis, Marinka Zitnik

NeurIPSW 2024 Small-Cohort GWAS Discovery with AI over Massive Functional Genomics Knowledge Graph Kexin Huang, Tony Zeng, Soner Koc, Alexandra Pettet, Martin Jinye Zhang, Jure Leskovec

NeurIPS 2023 High Dimensional, Tabular Deep Learning with an Auxiliary Knowledge Graph Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec

LoG 2023 The Second Learning on Graphs Conference: Preface Soledad Villar, Benjamin Chamberlain, Yuanqi Du, Hannes St"ark, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan

NeurIPS 2023 Uncertainty Quantification over Graph with Conformalized Graph Neural Networks Kexin Huang, Ying Jin, Emmanuel Candes, Jure Leskovec

NeurIPS 2022 Graphein - A Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks Arian Jamasb, Ramon Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom Blundell

ICMLW 2022 Graphein - A Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks Arian Rokkum Jamasb, Ramon Viñas Torné, Eric J Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lio, Tom Leon Blundell

NeurIPSW 2022 Tabular Deep Learning When $d \gg N$ by Using an Auxiliary Knowledge Graph Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec

LoG 2022 The First Learning on Graphs Conference: Preface Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle Li, Sofia Bourhim, Ilia Igashov

UAI 2022 Uncertainty-Aware Pseudo-Labeling for Quantum Calculations Kexin Huang, Vishnu Sresht, Brajesh Rai, Mykola Bordyuh

NeurIPSW 2021 Adaptive Pseudo-Labeling for Quantum Calculations Kexin Huang, Vishnu Sresht, Brajesh Rai, Mykola Bordyuh

AAAI 2020 CASTER: Predicting Drug Interactions with Chemical Substructure Representation Kexin Huang, Cao Xiao, Trong Nghia Hoang, Lucas Glass, Jimeng Sun

NeurIPS 2020 Graph Meta Learning via Local Subgraphs Kexin Huang, Marinka Zitnik