Yang, Yiming

93 publications

ICML 2025 Chaos Meets Attention: Transformers for Large-Scale Dynamical Prediction Yi He, Yiming Yang, Xiaoyuan Cheng, Hai Wang, Xiao Xue, Boli Chen, Yukun Hu

NeurIPS 2025 Enhancing Bioactivity Prediction via Spatial Emptiness Representation of Protein-Ligand Complex and Union of Multiple Pockets Zhiyuan Zhou, Yueming Yin, Yiming Yang, Yuguang Mu, Hoi-Yeung Li, Adams Wai-Kin Kong

NeurIPS 2025 Enhancing Training Data Attribution with Representational Optimization Weiwei Sun, Haokun Liu, Nikhil Kandpal, Colin Raffel, Yiming Yang

ICLRW 2025 HaluEval-Wild: Evaluating Hallucinations of Language Models in the Wild Zhiying Zhu, Yiming Yang, Zhiqing Sun

NeurIPS 2025 Improving Retrieval-Augmented Generation Through Multi-Agent Reinforcement Learning Yiqun Chen, Lingyong Yan, Weiwei Sun, Xinyu Ma, Yi Zhang, Shuaiqiang Wang, Dawei Yin, Yiming Yang, Jiaxin Mao

ICLR 2025 Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for LLM Problem-Solving Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, Yiming Yang

CVPRW 2025 Instance Feature Caching for Cross-Domain Few-Shot Object Detection Yali Huang, Jie Mei, Yiming Yang, Mi Guo, Mingyuan Jiu, Mingliang Xu

ICML 2025 Large Language Models Are Demonstration Pre-Selectors for Themselves Jiarui Jin, Yuwei Wu, Haoxuan Li, Xiaoting He, Weinan Zhang, Yiming Yang, Yong Yu, Jun Wang, Mengyue Yang

ICLR 2025 Lean-STaR: Learning to Interleave Thinking and Proving Haohan Lin, Zhiqing Sun, Sean Welleck, Yiming Yang

ICLR 2025 Learning Chaos in a Linear Way Xiaoyuan Cheng, Yi He, Yiming Yang, Xiao Xue, Sibo Cheng, Daniel Giles, Xiaohang Tang, Yukun Hu

ICML 2025 Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Shanda Li, Shinjae Yoo, Yiming Yang

CVPRW 2025 NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Results Yuqian Fu, Xingyu Qiu, Bin Ren, Yanwei Fu, Radu Timofte, Nicu Sebe, Ming-Hsuan Yang, Luc Van Gool, Kaijin Zhang, Qingpeng Nong, Xiugang Dong, Hong Gao, Xiangsheng Zhou, Jiancheng Pan, Yanxing Liu, Xiao He, Jiahao Li, Yuze Sun, Xiaomeng Huang, Zhenyu Zhang, Ran Ma, Yuhan Liu, Zijian Zhuang, Shuai Yi, Yixiong Zou, Lingyi Hong, Mingxi Chen, Runze Li, Xingdong Sheng, Wenqiang Zhang, Weisen Chen, Yongxin Yan, Xinguo Chen, Yuanjie Shao, Zhengrong Zuo, Nong Sang, Hao Wu, Haoran Sun, Shuming Hu, Yan Zhang, Zhiguang Shi, Yu Zhang, Chao Chen, Tao Wang, Da Feng, Linhai Zhuo, Ziming Lin, Yali Huang, Jie Me, Yiming Yang, Mi Guo, Mingyuan Jiu, Mingliang Xu, Maomao Xiong, Qunshu Zhang, Xinyu Cao, Yuqing Yang, Dianmo Sheng, Xuanpu Zhao, Zhiyu Li, Xuyang Ding, Wenqian Li

ICML 2025 Optimizing Temperature for Language Models with Multi-Sample Inference Weihua Du, Yiming Yang, Sean Welleck

ICML 2025 Regularized Langevin Dynamics for Combinatorial Optimization Shengyu Feng, Yiming Yang

AAAI 2025 SORREL: Suboptimal-Demonstration-Guided Reinforcement Learning for Learning to Branch Shengyu Feng, Yiming Yang

NeurIPS 2025 Safe and Stable Control via Lyapunov-Guided Diffusion Models Xiaoyuan Cheng, Xiaohang Tang, Yiming Yang

ICLR 2025 Self-Play Preference Optimization for Language Model Alignment Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu

ICLR 2025 Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo Shengyu Feng, Xiang Kong, Shuang Ma, Aonan Zhang, Dong Yin, Chong Wang, Ruoming Pang, Yiming Yang

ICLR 2025 TFG-Flow: Training-Free Guidance in Multimodal Generative Flow Haowei Lin, Shanda Li, Haotian Ye, Yiming Yang, Stefano Ermon, Yitao Liang, Jianzhu Ma

ICML 2025 Tensor-Var: Efficient Four-Dimensional Variational Data Assimilation Yiming Yang, Xiaoyuan Cheng, Daniel Giles, Sibo Cheng, Yi He, Xiao Xue, Boli Chen, Yukun Hu

AAAI 2025 Topo2Seq: Enhanced Topology Reasoning via Topology Sequence Learning Yiming Yang, Yueru Luo, Bingkun He, Erlong Li, Zhipeng Cao, Chao Zheng, Shuqi Mei, Zhen Li

NeurIPS 2024 AutoMix: Automatically Mixing Language Models Pranjal Aggarwal, Aman Madaan, Ankit Anand, Srividya Pranavi Potharaju, Swaroop Mishra, Pei Zhou, Aditya Gupta, Dheeraj Rajagopal, Karthik Kappaganthu, Yiming Yang, Shyam Upadhyay, Manaal Faruqui, Mausam

NeurIPS 2024 Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision Zhiqing Sun, Longhui Yu, Yikang Shen, Weiyang Liu, Yiming Yang, Sean Welleck, Chuang Gan

ICLR 2024 Functional Interpolation for Relative Positions Improves Long Context Transformers Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontanon, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli

ICML 2024 In-Context Principle Learning from Mistakes Tianjun Zhang, Aman Madaan, Luyu Gao, Steven Zheng, Swaroop Mishra, Yiming Yang, Niket Tandon, Uri Alon

ICMLW 2024 In-Context Principle Learning from Mistakes Tianjun Zhang, Aman Madaan, Luyu Gao, Steven Zhang, Swaroop Mishra, Yiming Yang, Niket Tandon, Uri Alon

NeurIPSW 2024 Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for LLM Problem-Solving Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, Yiming Yang

NeurIPSW 2024 Lean-STaR: Learning to Interleave Thinking and Proving Haohan Lin, Zhiqing Sun, Sean Welleck, Yiming Yang

ICLR 2024 Learning Performance-Improving Code Edits Alexander G Shypula, Aman Madaan, Yimeng Zeng, Uri Alon, Jacob R. Gardner, Yiming Yang, Milad Hashemi, Graham Neubig, Parthasarathy Ranganathan, Osbert Bastani, Amir Yazdanbakhsh

AISTATS 2024 Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamas Sarlos, Thomas Weingarten, Adrian Weller

ICLR 2024 SALMON: Self-Alignment with Instructable Reward Models Zhiqing Sun, Yikang Shen, Hongxin Zhang, Qinhong Zhou, Zhenfang Chen, David Daniel Cox, Yiming Yang, Chuang Gan

ICLRW 2024 SELF-IMAGINE: Effective Unimodal Reasoning with Multimodal Models Using Self-Imagination Syeda Nahida Akter, Aman Madaan, Sangwu Lee, Yiming Yang, Eric Nyberg

ICMLW 2024 Self-Play Preference Optimization for Language Model Alignment Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu

NeurIPSW 2024 Self-Play Preference Optimization for Language Model Alignment Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu

ICML 2023 A Neural PDE Solver with Temporal Stencil Modeling Zhiqing Sun, Yiming Yang, Shinjae Yoo

ICMLW 2023 Accelerating Diffusion-Based Combinatorial Optimization Solvers by Progressive Distillation Junwei Huang, Zhiqing Sun, Yiming Yang

NeurIPSW 2023 AutoMix: Mixing Models with Few-Shot Self and Meta Verification Aman Madaan, Pranjal Aggarwal, Ankit Anand, Srividya Pranavi Potharaju, Swaroop Mishra, Pei Zhou, Aditya Gupta, Dheeraj Rajagopal, Yiming Yang, Shyam Upadhyay, Mausam, Manaal Faruqui

NeurIPS 2023 DIFUSCO: Graph-Based Diffusion Solvers for Combinatorial Optimization Zhiqing Sun, Yiming Yang

ICML 2023 PAL: Program-Aided Language Models Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, Graham Neubig

NeurIPS 2023 Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision Zhiqing Sun, Yikang Shen, Qinhong Zhou, Hongxin Zhang, Zhenfang Chen, David Cox, Yiming Yang, Chuang Gan

ICLR 2023 Recitation-Augmented Language Models Zhiqing Sun, Xuezhi Wang, Yi Tay, Yiming Yang, Denny Zhou

NeurIPS 2023 Self-Refine: Iterative Refinement with Self-Feedback Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark

NeurIPS 2022 DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems Ruizhong Qiu, Zhiqing Sun, Yiming Yang

AAAI 2022 JAKET: Joint Pre-Training of Knowledge Graph and Language Understanding Donghan Yu, Chenguang Zhu, Yiming Yang, Michael Zeng

ICLR 2022 Sparse Attention with Learning to Hash Zhiqing Sun, Yiming Yang, Shinjae Yoo

ECML-PKDD 2021 Enhancing Summarization with Text Classification via Topic Consistency Jingzhou Liu, Yiming Yang

ICLR 2021 Meta Back-Translation Hieu Pham, Xinyi Wang, Yiming Yang, Graham Neubig

ICCV 2021 Rethinking Transformer-Based Set Prediction for Object Detection Zhiqing Sun, Shengcao Cao, Yiming Yang, Kris M. Kitani

ICML 2020 An EM Approach to Non-Autoregressive Conditional Sequence Generation Zhiqing Sun, Yiming Yang

ICLR 2020 Cross-Lingual Alignment vs Joint Training: A Comparative Study and a Simple Unified Framework Zirui Wang, Jiateng Xie, Ruochen Xu, Yiming Yang, Graham Neubig, Jaime Carbonell

NeurIPS 2020 Funnel-Transformer: Filtering Out Sequential Redundancy for Efficient Language Processing Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le

ECML-PKDD 2020 Graph-Revised Convolutional Network Donghan Yu, Ruohong Zhang, Zhengbao Jiang, Yuexin Wu, Yiming Yang

ICLR 2020 Pre-Training Tasks for Embedding-Based Large-Scale Retrieval Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar

ICLR 2019 DARTS: Differentiable Architecture Search Hanxiao Liu, Karen Simonyan, Yiming Yang

AISTATS 2019 Implicit Kernel Learning Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabas Poczos

ICLR 2019 Kernel Change-Point Detection with Auxiliary Deep Generative Models Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos

NeurIPS 2019 Re-Examination of the Role of Latent Variables in Sequence Modeling Guokun Lai, Zihang Dai, Yiming Yang, Shinjae Yoo

AAAI 2019 Switch-Based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning Yuexin Wu, Xiujun Li, Jingjing Liu, Jianfeng Gao, Yiming Yang

NeurIPS 2019 XLNet: Generalized Autoregressive Pretraining for Language Understanding Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V Le

ICML 2017 Analogical Inference for Multi-Relational Embeddings Hanxiao Liu, Yuexin Wu, Yiming Yang

AAAI 2017 Cross-Domain Kernel Induction for Transfer Learning Wei-Cheng Chang, Yuexin Wu, Hanxiao Liu, Yiming Yang

IJCAI 2017 Data-Driven Random Fourier Features Using Stein Effect Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos

NeurIPS 2017 MMD GAN: Towards Deeper Understanding of Moment Matching Network Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabas Poczos

NeurIPS 2016 Adaptive Smoothed Online Multi-Task Learning Keerthiram Murugesan, Hanxiao Liu, Jaime Carbonell, Yiming Yang

ICML 2016 Cross-Graph Learning of Multi-Relational Associations Hanxiao Liu, Yiming Yang

JAIR 2016 Learning Concept Graphs from Online Educational Data Hanxiao Liu, Wanli Ma, Yiming Yang, Jaime G. Carbonell

AISTATS 2016 Semi-Supervised Learning with Adaptive Spectral Transform Hanxiao Liu, Yiming Yang

ICML 2015 Bipartite Edge Prediction via Transductive Learning over Product Graphs Hanxiao Liu, Yiming Yang

UAI 2014 Transformation-Based Probabilistic Clustering with Supervision Siddharth Gopal, Yiming Yang

ICML 2014 Von Mises-Fisher Clustering Models Siddharth Gopal, Yiming Yang

ICML 2013 Distributed Training of Large-Scale Logistic Models Siddharth Gopal, Yiming Yang

NeurIPS 2012 Bayesian Models for Large-Scale Hierarchical Classification Siddharth Gopal, Yiming Yang, Bing Bai, Alexandru Niculescu-mizil

MLJ 2012 Multilabel Classification with Meta-Level Features in a Learning-to-Rank Framework Yiming Yang, Siddharth Gopal

ICML 2010 Active Learning for Multi-Task Adaptive Filtering Abhay Harpale, Yiming Yang

ECML-PKDD 2009 Protein Identification from Tandem Mass Spectra with Probabilistic Language Modeling Yiming Yang, Abhay Harpale, Subramaniam Ganapathy

MLJ 2008 Flexible Latent Variable Models for Multi-Task Learning Jian Zhang, Zoubin Ghahramani, Yiming Yang

NeurIPS 2005 From Lasso Regression to Feature Vector Machine Fan Li, Yiming Yang, Eric P. Xing

NeurIPS 2005 Learning Multiple Related Tasks Using Latent Independent Component Analysis Jian Zhang, Zoubin Ghahramani, Yiming Yang

AAAI 2005 Using Modified Lasso Regression to Learn Large Undirected Graphs in a Probabilistic Framework Fan Li, Yiming Yang

NeurIPS 2004 A Probabilistic Model for Online Document Clustering with Application to Novelty Detection Jian Zhang, Zoubin Ghahramani, Yiming Yang

ICML 2004 Probabilistic Score Estimation with Piecewise Logistic Regression Jian Zhang, Yiming Yang

JMLR 2004 RCV1: A New Benchmark Collection for Text Categorization Research David D. Lewis, Yiming Yang, Tony G. Rose, Fan Li

ECML-PKDD 2004 The Enron Corpus: A New Dataset for Email Classification Research Bryan Klimt, Yiming Yang

ICML 2003 A Loss Function Analysis for Classification Methods in Text Categorization Fan Li, Yiming Yang

ICML 2003 Modified Logistic Regression: An Approximation to SVM and Its Applications in Large-Scale Text Categorization Jian Zhang, Rong Jin, Yiming Yang, Alexander G. Hauptmann

AAAI 2002 Stochastic Link and Group Detection Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider, Yiming Yang

ICML 2001 Hypertext Categorization Using Hyperlink Patterns and Meta Data Rayid Ghani, Seán Slattery, Yiming Yang

ICML 2000 Combining Multiple Learning Strategies for Effective Cross Validation Yiming Yang, Tom Ault, Thomas Pierce

MLJ 2000 Special Issue of Machine Learning on Information Retrieval - Introduction Jaime G. Carbonell, Yiming Yang, William W. Cohen

ICML 1997 A Comparative Study on Feature Selection in Text Categorization Yiming Yang, Jan O. Pedersen

IJCAI 1997 Translingual Information Retrieval: A Comparative Evaluation Jaime G. Carbonell, Yiming Yang, Robert E. Frederking, Ralf D. Brown, Yibing Geng, Danny Lee

IJCAI 1987 Combining Prediction, Syntactic Analysis and Semantic Analysis in Chinese Sentence Analysis Yiming Yang

IJCAI 1985 Partial Constraints in Chinese Analysis Yiming Yang, Shuji Doshita, Toyoaki Nishida