Zhang, Tianjun

36 publications

ICML 2025 Copilot Arena: A Platform for Code LLM Evaluation in the Wild Wayne Chi, Valerie Chen, Anastasios Nikolas Angelopoulos, Wei-Lin Chiang, Aditya Mittal, Naman Jain, Tianjun Zhang, Ion Stoica, Chris Donahue, Ameet Talwalkar

ICLR 2025 LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, Ion Stoica

ICLR 2025 SuperCorrect: Advancing Small LLM Reasoning with Thought Template Distillation and Self-Correction Ling Yang, Zhaochen Yu, Tianjun Zhang, Minkai Xu, Joseph E. Gonzalez, Bin Cui, Shuicheng Yan

ICLR 2024 AgentBench: Evaluating LLMs as Agents Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, Jie Tang

NeurIPS 2024 Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E. Gonzalez, Bin Cui

NeurIPS 2024 Gorilla: Large Language Model Connected with Massive APIs Shishir G. Patil, Tianjun Zhang, Xin Wang, Joseph E. Gonzalez

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

ICLR 2024 LLM-Assisted Code Cleaning for Training Accurate Code Generators Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E. Gonzalez, Koushik Sen, Ion Stoica

WACV 2024 Multitask Vision-Language Prompt Tuning Sheng Shen, Shijia Yang, Tianjun Zhang, Bohan Zhai, Joseph E. Gonzalez, Kurt Keutzer, Trevor Darrell

ICML 2024 R2E: Turning Any GitHub Repository into a Programming Agent Environment Naman Jain, Manish Shetty, Tianjun Zhang, King Han, Koushik Sen, Ion Stoica

ICLRW 2024 R2E: Turning Any GitHub Repository into a Programming Agent Environment Naman Jain, Manish Shetty, Tianjun Zhang, King Han, Koushik Sen, Ion Stoica

ICMLW 2024 Recursive Introspection: Teaching Foundation Model Agents How to Self-Improve Yuxiao Qu, Tianjun Zhang, Naman Garg, Aviral Kumar

ICMLW 2024 Recursive Introspection: Teaching LLM Agents How to Self-Improve Yuxiao Qu, Tianjun Zhang, Naman Garg, Aviral Kumar

ICMLW 2024 Recursive Introspection: Teaching LLM Agents How to Self-Improve Yuxiao Qu, Tianjun Zhang, Naman Garg, Aviral Kumar

ICMLW 2024 Recursive Introspection: Teaching LLM Agents How to Self-Improve Yuxiao Qu, Tianjun Zhang, Naman Garg, Aviral Kumar

NeurIPS 2024 Recursive Introspection: Teaching Language Model Agents How to Self-Improve Yuxiao Qu, Tianjun Zhang, Naman Garg, Aviral Kumar

ICLR 2023 Efficient Planning in a Compact Latent Action Space Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian

UAI 2023 Energy-Based Predictive Representations for Partially Observed Reinforcement Learning Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai

NeurIPSW 2023 Improving Code Style for Accurate Code Generation Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E. Gonzalez, Koushik Sen, Ion Stoica

ICLR 2023 Latent Variable Representation for Reinforcement Learning Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai

ICLR 2023 Spectral Decomposition Representation for Reinforcement Learning Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai

ICLR 2023 TEMPERA: Test-Time Prompt Editing via Reinforcement Learning Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez

ICML 2023 The Wisdom of Hindsight Makes Language Models Better Instruction Followers Tianjun Zhang, Fangchen Liu, Justin Wong, Pieter Abbeel, Joseph E. Gonzalez

UAI 2022 A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai

ICLR 2022 C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez

NeurIPS 2022 Contrastive Learning as Goal-Conditioned Reinforcement Learning Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov

NeurIPSW 2022 Efficient Planning in a Compact Latent Action Space Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian

ICML 2022 Making Linear MDPs Practical via Contrastive Representation Learning Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph Gonzalez, Dale Schuurmans, Bo Dai

ICLR 2022 Multi-Objective Optimization by Learning Space Partition Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian

NeurIPSW 2021 C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez

NeurIPSW 2021 Graph Backup: Data Efficient Backup Exploiting Markovian Data Zhengyao Jiang, Tianjun Zhang, Robert Kirk, Tim Rocktäschel, Edward Grefenstette

NeurIPS 2021 Learning Space Partitions for Path Planning Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E Gonzalez, Dan Klein, Yuandong Tian

NeurIPS 2021 MADE: Exploration via Maximizing Deviation from Explored Regions Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E Gonzalez, Stuart J. Russell

NeurIPS 2021 NovelD: A Simple yet Effective Exploration Criterion Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E Gonzalez, Yuandong Tian

NeurIPS 2019 ANODEV2: A Coupled Neural ODE Framework Tianjun Zhang, Zhewei Yao, Amir Gholami, Joseph E Gonzalez, Kurt Keutzer, Michael W. Mahoney, George Biros