ML Anthology

He, Junxian

37 publications

ICLR 2026 Learn to Reason Efficiently with Adaptive Length-Based Reward Shaping Wei Liu, Ruochen Zhou, Yiyun Deng, Yuzhen Huang, Junteng Liu, Yuntian Deng, Yizhe Zhang, Junxian He
ICLR 2026 Mirage or Method? How Model–Task Alignment Induces Divergent RL Conclusions Haoze Wu, Cheng Wang, Wenshuo Zhao, Junxian He
ICLR 2026 Pushing Test-Time Scaling Limits of Deep Search with Asymmetric Verification Weihao Zeng, Keqing He, Chuqiao Kuang, Xiaoguang Li, Junxian He
ICLR 2026 SWE-RM: Execution-Free Feedback for Software Engineering Agents KaShun Shum, Binyuan Hui, Jiawei Chen, Lei Zhang, X. W., Jiaxi Yang, Yuzhen Huang, Junyang Lin, Junxian He
ICLR 2026 The Tool Decathlon: Benchmarking Language Agents for Diverse, Realistic, and Long-Horizon Task Execution Junlong Li, Wenshuo Zhao, Jian Zhao, Weihao Zeng, Haoze Wu, Xiaochen Wang, Rui Ge, Yuxuan Cao, Yuzhen Huang, Wei Liu, Junteng Liu, Zhaochen Su, Yiyang Guo, Fan Zhou, Lueyang Zhang, Juan Michelini, Xingyao Wang, Xiang Yue, Shuyan Zhou, Graham Neubig, Junxian He
ICLR 2025 B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners Weihao Zeng, Yuzhen Huang, Lulu Zhao, Yijun Wang, Zifei Shan, Junxian He
ICML 2025 Bring Reason to Vision: Understanding Perception and Reasoning Through Model Merging Shiqi Chen, Jinghan Zhang, Tongyao Zhu, Wei Liu, Siyang Gao, Miao Xiong, Manling Li, Junxian He
ICML 2025 CodeIO: Condensing Reasoning Patterns via Code Input-Output Prediction Junlong Li, Daya Guo, Dejian Yang, Runxin Xu, Yu Wu, Junxian He
ICLRW 2025 Diving into Self-Evolve Training for Multimodal Reasoning Wei Liu, Junlong Li, Xiwen Zhang, Fan Zhou, Yu Cheng, Junxian He
ICML 2025 Diving into Self-Evolving Training for Multimodal Reasoning Wei Liu, Junlong Li, Xiwen Zhang, Fan Zhou, Yu Cheng, Junxian He
ICLR 2025 Non-Myopic Generation of Language Models for Reasoning and Planning Chang Ma, Haiteng Zhao, Junlei Zhang, Junxian He, Lingpeng Kong
ICML 2025 Predictive Data Selection: The Data That Predicts Is the Data That Teaches Kashun Shum, Yuzhen Huang, Hongjian Zou, Qi Ding, Yixuan Liao, Xiaoxin Chen, Qian Liu, Junxian He
NeurIPS 2025 SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond Junteng Liu, Yuanxiang Fan, Jiang Zhuo, Han Ding, Yongyi Hu, Chi Zhang, Yiqi Shi, Shitong Weng, Aili Chen, Shiqi Chen, Mozhi Zhang, Pengyu Zhao, Junxian He
ICML 2025 Why Is Spatial Reasoning Hard for VLMs? an Attention Mechanism Perspective on Focus Areas Shiqi Chen, Tongyao Zhu, Ruochen Zhou, Jinghan Zhang, Siyang Gao, Juan Carlos Niebles, Mor Geva, Junxian He, Jiajun Wu, Manling Li
NeurIPS 2024 AgentBoard: An Analytical Evaluation Board of Multi-Turn LLM Agents Chang Ma, Junlei Zhang, Zhihao Zhu, Cheng Yang, Yujiu Yang, Yaohui Jin, Zhenzhong Lan, Lingpeng Kong, Junxian He
ICLRW 2024 AgentBoard: An Analytical Evaluation Board of Multi-Turn LLM Agents Chang Ma, Junlei Zhang, Zhihao Zhu, Cheng Yang, Yujiu Yang, Yaohui Jin, Zhenzhong Lan, Lingpeng Kong, Junxian He
ICLR 2024 Can LLMs Express Their Uncertainty? an Empirical Evaluation of Confidence Elicitation in LLMs Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu, Junxian He, Bryan Hooi
NeurIPS 2024 DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving Yuxuan Tong, Xiwen Zhang, Rui Wang, Ruidong Wu, Junxian He
ICML 2024 In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation Shiqi Chen, Miao Xiong, Junteng Liu, Zhengxuan Wu, Teng Xiao, Siyang Gao, Junxian He
ICLRW 2024 In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation Shiqi Chen, Miao Xiong, Junteng Liu, Zhengxuan Wu, Teng Xiao, Siyang Gao, Junxian He
NeurIPSW 2024 Math for AI: On the Generalization of Learning Mathematical Problem Solving Ruochen Zhou, Minrui Xu, Shiqi Chen, Junteng Liu, Yunqi Li, Xinxin Lin, Zhengyu Chen, Junxian He
NeurIPS 2024 Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in LLMs Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei Koh, Bryan Hooi
ICLRW 2024 Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei Koh, Bryan Hooi
ICLR 2024 What Makes Good Data for Alignment? a Comprehensive Study of Automatic Data Selection in Instruction Tuning Wei Liu, Weihao Zeng, Keqing He, Yong Jiang, Junxian He
NeurIPS 2023 C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, Junlei Zhang, Jinghan Zhang, Tangjun Su, Junteng Liu, Chuancheng Lv, Yikai Zhang, Jiayi Lei, Yao Fu, Maosong Sun, Junxian He
NeurIPS 2023 Composing Parameter-Efficient Modules with Arithmetic Operation Jinghan Zhang, Shiqi Chen, Junteng Liu, Junxian He
NeurIPS 2023 FELM: Benchmarking Factuality Evaluation of Large Language Models Shiqi Chen, Yiran Zhao, Jinghan Zhang, I-Chun Chern, Siyang Gao, Pengfei Liu, Junxian He
ICLR 2023 Mega: Moving Average Equipped Gated Attention Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, Luke Zettlemoyer
NeurIPS 2023 Self-Evaluation Guided Beam Search for Reasoning Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, James Xu Zhao, Min-Yen Kan, Junxian He, Michael Xie
ICLR 2022 Capturing Structural Locality in Non-Parametric Language Models Frank F. Xu, Junxian He, Graham Neubig, Vincent Josua Hellendoorn
ICML 2022 Neuro-Symbolic Language Modeling with Automaton-Augmented Retrieval Uri Alon, Frank Xu, Junxian He, Sudipta Sengupta, Dan Roth, Graham Neubig
ICMLW 2022 Neuro-Symbolic Language Modeling with Automaton-Augmented Retrieval Uri Alon, Frank F. Xu, Junxian He, Sudipta Sengupta, Dan Roth, Graham Neubig
ICLR 2022 Towards a Unified View of Parameter-Efficient Transfer Learning Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig
ICLR 2020 A Probabilistic Formulation of Unsupervised Text Style Transfer Junxian He, Xinyi Wang, Graham Neubig, Taylor Berg-Kirkpatrick
NeurIPS 2020 Learning Sparse Prototypes for Text Generation Junxian He, Taylor Berg-Kirkpatrick, Graham Neubig
ICLR 2020 Revisiting Self-Training for Neural Sequence Generation Junxian He, Jiatao Gu, Jiajun Shen, Marc'Aurelio Ranzato
ICLR 2019 Lagging Inference Networks and Posterior Collapse in Variational Autoencoders Junxian He, Daniel Spokoyny, Graham Neubig, Taylor Berg-Kirkpatrick