I am a member of technical staff at Thinking Machines Lab. Previously, I was a senior research scientist at NVIDIA Research. I was a visiting scholar at University of Illinois at Urbana-Champaign, working with Prof. Heng Ji. I received my Ph.D. in 2023 advised by Prof. Tong Zhang. My research focuses on developing methods to scale up post-training and reinforcement learning for large language models, pushing the frontier of more capable, general-purpose AI agents through data-centric design.

News

• Excited to join Thinking Machines Lab as a member of technical staff!
• Our ClimbMix becomes the default pretraining dataset used in Andrej Karpathy's NanoChat speedrun.
• Four papers got accepted by ICLR 2026!
• Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text.
• GDPO: Group reward-Decoupled Normalization Policy Optimization (GDPO), a new multi-reward RL algorithm that consistently improves per-reward convergence over GRPO.
• ToolOrchestra: An RL-based framework for training small orchestrators to orchestrate large LLMs and tools. Our Orchestrator-8B outperforms GPT-5 on HLE (37.1% vs 35.1%) while being 2.5x faster and 70% cheaper, and ranked #1 on GAIA benchmark. [Homepage] [Model] [Data] [Code]
• ProfBench: A professional reasoning benchmark with 7,000+ expert-written rubrics from 38 domain experts across finance, consulting, chemistry, and physics is released!
• BroRL: Scaling Reinforcement Learning via Broadened Exploration is released!
• Fast-dLLM v2: Efficient Block-Diffusion LLM is released!
• Open-sourced NVIDIA-Nemotron-Nano-v2-9B: our next-generation efficient hybrid model which is 6x faster than Qwen3-8B at reasoning tasks.
• ProRL v2 is released!
• Introducing ProRL, a novel training recipe that scales RL to 2k+ steps, powering the world's leading 1.5B reasoning model: Nemotron-Research-Reasoning-Qwen-1.5B.
• Excited to share Fast-dLLM: 27.6x Faster Diffusion LLMs with KV Cache & Parallel Decoding.

More News

Selected Publications (Full List)

1. Zhilin Wang, Jaehun Jung, Ximing Lu, , Ellie Evans, Jiaqi Zeng, Pavlo Molchanov, Yejin Choi, Jan Kautz, Yi Dong
   ProfBench: Multi-Domain Rubrics requiring Professional Knowledge to Answer and Judge NEW
   ICLR 2026
2. , Yu Yang, Yonggan Fu, Xin Dong, Dan SU, Markus Kliegl, Zijia Chen, Peter Belcak, Yoshi Suhara, Hongxu Yin, Mostofa Patwary, Yingyan Celine Lin, Jan Kautz, Pavlo Molchanov
   Nemotron-CLIMB: Clustering-based Iterative Data Mixture Bootstrapping for Language Model Pre-training
   NeurIPS 2025 Datasets and Benchmarks Track
3. Mingjie Liu, , Ximing Lu, Jian Hu, Xin Dong, Yejin Choi, Jan Kautz, Yi Dong
   ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
   NeurIPS 2025
4. Yonggan Fu, Xin Dong, , Matthijs Van keirsbilck, Hanrong Ye, Wonmin Byeon, Yashaswi Karnati, Lucas Liebenwein, Maksim Khadkevich, Alexander Keller, Jan Kautz, Yingyan Celine Lin, Pavlo Molchanov
   Nemotron-Flash: Towards Latency-Optimal Hybrid Small Language Models
   NeurIPS 2025
5. Xin Xu, Qiyun Xu, Tong Xiao, Tianhao Chen, Yuchen Yan, Jiaxin Zhang, , Can Yang, Yang Wang
   UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models
   ICML 2025
6. Hanning Zhang, Pengcheng Wang, , Yong Lin, Rui Pan, Hanze Dong, Dylan Zhang, Pavlo Molchanov, Tong Zhang
   Entropy-Regularized Process Reward Model
   TMLR 2025
7. Xin Xu, , Can Yang, Yang Wang
   Can We Verify Step by Step for Incorrect Answer Detection?
   IJCAI 2025
8. Xin Dong, Yonggan Fu, , Wonmin Byeon, Zijia Chen, Ameya Sunil Mahabaleshwarkar, Shih-Yang Liu, Matthijs Van Keirsbilck, Min-Hung Chen, Yoshi Suhara, Yingyan Lin, Jan Kautz, Pavlo Molchanov
   Hymba: A Hybrid-head Architecture for Small Language Models
   ICLR 2025
9. Rui Pan, Xiang Liu, , Renjie Pi, Jipeng Zhang, Chi Han, Tong Zhang
   LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
   NeurIPS 2024
10. Tianyang Xu, Shujin Wu, , Xiaoze Liu, Xingyao Wang, Yangyi Chen, Jing Gao
    SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales
    EMNLP 2024
11. Yong Lin, Hangyu Lin, Wei Xiong, , Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Heng Ji, Yuan Yao, Tong Zhang
    Mitigating the Alignment Tax of RLHF
    EMNLP 2024
12. Ruida Wang, Jipeng Zhang, Yizhen Jia, Rui Pan, , Renjie Pi, Tong Zhang
    TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts
    EMNLP 2024
13. , Pengcheng Wang, Yong Lin, Tong Zhang.
    Active Prompting with Chain-of-Thought for Large Language Models
    ACL 2024
14. Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, , Shuang Qiu, Han Zhao, Tong Zhang
    Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards
    ACL 2024
15. Rui Pan*, Shuo Xing*, , Wenhe Sun*, Xiang Liu, Kashun Shum, Renjie Pi, Jipeng Zhang, Tong Zhang
    Plum: Prompt Learning using Metaheuristic
    Findings of ACL 2024
16. , Rui Pan*, Hanze Dong*, Ka Shun Shum, Jipeng Zhang, Wei Xiong, Tong Zhang
    LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models
    NAACL 2024 Demo Track Best Demo Paper
17. Hanning Zhang*, , Yong Lin*, Yi R. Fung, Qing Lian, Xingyao Wang, Yangyi Chen, Heng Ji, Tong Zhang
    R-Tuning: Instructing Large Language Models to Say `I Don't Know'
    NAACL 2024 Outstanding Paper
18. Xu Liu, Junfeng Hu, Yuan Li, , Yuxuan Liang, Bryan Hooi, Roger Zimmermann
    UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting
    WWW 2024
19. Hanze Dong*, Wei Xiong*, Deepanshu Goyal, Rui Pan, , Jipeng Zhang, Kashun Shum, Tong Zhang.
    RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment
    TMLR
20. Kashun Shum*, , Tong Zhang.
    Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data
    Findings of EMNLP 2023
21. Renjie Pi*, Jiahui Gao*, , Rui Pan, Hanze Dong, Jipeng Zhang, Lewei Yao, Jianhua Han, Hang Xu, Lingpeng Kong, Tong Zhang
    DetGPT: Detect What You Need via Reasoning
    EMNLP 2023
22. , Yongyu Lei*, Liangming Pan, Tianqing Fang, Wangchunshu Zhou, Sedrick Scott Keh, Min-Yen Kan, Tong Zhang.
    Doolittle: Benchmarks and Corpora for Academic Writing Formalization
    EMNLP 2023
23. Zhihong Chen*, , Benyou Wang, Guanbin Li, Xiang Wan.
    Towards Unifying Medical Vision-and-Language Pre-training via Soft Prompts
    ICCV 2023
24. , Tianyang Xu*, Ruijia Xu, Jiawei Wang, Tong Zhang.
    Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models' Memories
    ACL 2023
25. Zhihong Chen, Guiming Hardy Chen, , Xiang Wan, Benyou Wang.
    On the Difference of BERT-style and CLIP-style Text Encoders
    Findings of ACL 2023
26. , Wangchunshu Zhou, Xinsong Zhang, Jiawei Wang.
    Write and Paint: Generative Vision-Language Models are Unified Modal Learners
    ICLR 2023
27. , Zhichao Huang, Ruijia Xu, Xuechun Li, Yong Lin, Xiao Zhou, Tong Zhang.
    Black-box Prompt Learning for Pre-trained Language Models
    TMLR
28. , Sedrick Scott Keh*, Liangming Pan, Zhiliang Tian, Yan Song, Tong Zhang.
    Hashtag-Guided Low-Resource Tweet Classification
    WWW 2023
29. Wangchunshu Zhou*, Yan Zeng*, , Xinsong Zhang*.
    VLUE: A Multi-Task Benchmark for Evaluating Vision-Language Models
    ICML 2022
30. Xiao Zhou, Weizhong Zhang, Zonghao Chen, , Tong Zhang.
    Efficient Neural Network Training via Forward and Backward Propagation Sparsification
    NeurIPS 2021
31. , Ruijia Xu, Hongjin Su, Yilei Jiang, Yan Song, Tong Zhang.
    Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adaptation
    ACL 2021
32. , Xinwei Shen*, KaShun SHUM, Yan Song, Tong Zhang.
    TILGAN: Transformer-based Implicit Latent GAN for Diverse and Coherent Text Generation
    Findings of ACL 2021
33. , Jiaxin Bai, Yan Song, Tong Zhang, and Yonggang Wang.
    ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
    Findings of EMNLP 2020

Recent Talks

• [2025/11] Invited Talk @ University of Virginia on ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in LLMs. Hosted by Prof. Yu Meng
• [2024/11] Invited Lecture @ University of Michigan, Ann Arbor, CSE 595: Natural Language Processing. Sharing hybrid small language models hosted by Dr. Ziqiao Ma and Prof. Joyce Y. Chai
• [2023/10] Invited Lecture @ University of Toronto, graduate NLP course (CSC401/2511). Hosted by Prof. Annie Lee
• [2023/08] Invited Talk @ CVMI Lab, The University of Hong Kong. Hosted by Prof. Xiaojuan Qi
• [2023/06] Invited Talk @ University of Toronto. Hosted by Prof. Qiang Sun
• [2023/06] Invited Talk @ Shanghai AI Lab [Recording]
• [2023/05] Invited Talk @ Stanford University. Hosted by Prof. Mert Pilanci

Honors and Awards

• Best Demo Paper at NAACL 2024
• Outstanding Paper Award at NAACL 2024
• First Runner-up, School of Engineering PhD Research Excellence Award 2024, HKUST
• HKUST Overseas Research Award, 2023
• HKUST RedBird PhD Scholarship, 2021
• Hong Kong PhD Fellowship, 2021-2024
• EMNLP 2020, SIGIR 2020, ACL 2020 Student Volunteer, 2020
• Merit Student of Beijing, 2019
• Outstanding Graduate Student of Beijing, 2019
• Top 10 Talent Nomination Award (Only 20 in ~2000), 2018
• Meritorious Winner, Interdisciplinary Contest in Modeling (ICM), 2018
• Runner-up, World Robot Olympiad (WRO), New Delhi, India, 2016

Experience

Academic Service

• Demo Track Chair: NAACL 2025
• Area Chair / Action Editor: ACL ARR, ACL 2024 Workshop Towards Knowledgeable Language Models, The 2nd Workshop on Knowledgeable Foundation Models @ AAAI 25
• Journal Reviewer: Transactions on Machine Learning Research (TMLR), Data-centric Machine Learning Research (DMLR), International Journal of Computer Vision (IJCV), Transactions on Knowledge Discovery from Data (TKDD), SIAM Journal on Mathematics of Data Science (SIMODS)
• Conference Reviewer: ACL ARR, ACL, ICLR, EMNLP, NAACL, NeurIPS, ICML, WWW, KDD, AAAI, IJCAI, EACL, COLM, COLING, WSDM
• Volunteer: EMNLP 2020, SIGIR 2020, ACL 2020

Miscellaneous

• I used to be an amateur long-distance runner. Whenever I am not doing research, I love swimming, kayaking, windsurfing, dinghy sailing, and stand up paddling!
• As the captain, I organized a team to participate in the World Robot Olympiad (WRO) and won the second place in India.