Yi Dong

According to our database, Yi Dong authored at least 22 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

ProRL Agent: Rollout-as-a-Service for RL Training of Multi-Turn LLM Agents.

Hao Zhang, Mingjie Liu, Shaokun Zhang, Song Han, Jian Hu, Zhenghui Jin, Yuchi Zhang, Shizhe Diao, Ximing Lu, Binfeng Xu, Zhiding Yu, Jan Kautz, Yi Dong

CoRR, March, 2026

PhyCritic: Multimodal Critic Models for Physical AI.

Tianyi Xiong, Shihao Wang, Guilin Liu, Yi Dong, Ming Li, Heng Huang, Jan Kautz, Zhiding Yu

CoRR, February, 2026

Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text.

Ximing Lu, David Acuna, Jaehun Jung, Jian Hu, Di Zhang, Shizhe Diao, Yunheng Zou, Shaokun Zhang, Brandon Cui, Mingjie Liu, Hyunwoo Kim, Prithviraj Ammanabrolu, Jan Kautz, Yi Dong, Yejin Choi

CoRR, January, 2026

2025

ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration.

Hongjin Su, Shizhe Diao, Ximing Lu, Mingjie Liu, Jiacheng Xu, Xin Dong, Yonggan Fu, Peter Belcak, Hanrong Ye, Hongxu Yin, Yi Dong, Evelina Bakhturina, Tao Yu, Yejin Choi, Jan Kautz, Pavlo Molchanov

CoRR, November, 2025

ProfBench: Multi-Domain Rubrics requiring Professional Knowledge to Answer and Judge.

Zhilin Wang, Jaehun Jung, Ximing Lu, Shizhe Diao, Ellie Evans, Jiaqi Zeng, Pavlo Molchanov, Yejin Choi, Jan Kautz, Yi Dong

CoRR, October, 2025

BroRL: Scaling Reinforcement Learning via Broadened Exploration.

Jian Hu, Mingjie Liu, Ximing Lu, Fang Wu, Zaïd Harchaoui, Shizhe Diao, Yejin Choi, Pavlo Molchanov, June Yang, Jan Kautz, Yi Dong

CoRR, October, 2025

RLBFF: Binary Flexible Feedback to bridge between Human Feedback & Verifiable Rewards.

Zhilin Wang, Jiaqi Zeng, Olivier Delalleau, Ellie Evans, Daniel Egert, Hoo-Chang Shin, Felipe Soares, Yi Dong, Oleksii Kuchaiev

CoRR, September, 2025

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training.

Mingjie Liu, Shizhe Diao, Jian Hu, Ximing Lu, Xin Dong, Hao Zhang, Alexander Bukharin, Shaokun Zhang, Jiaqi Zeng, Makesh Narsimhan Sreedhar, Gerald Shen, David Mosallanezhad, Di Zhang, Jonas Yang, June Yang, Oleksii Kuchaiev, Guilin Liu, Zhiding Yu, Pavlo Molchanov, Yejin Choi, Jan Kautz, Yi Dong

CoRR, July, 2025

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models.

Mingjie Liu, Shizhe Diao, Ximing Lu, Jian Hu, Xin Dong, Yejin Choi, Jan Kautz, Yi Dong

CoRR, May, 2025

HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages.

Zhilin Wang, Jiaqi Zeng, Olivier Delalleau, Hoo-Chang Shin, Felipe Soares, Alexander Bukharin, Ellie Evans, Yi Dong, Oleksii Kuchaiev

CoRR, May, 2025

Nemotron-Research-Tool-N1: Exploring Tool-Using Language Models with Reinforced Reasoning.

Shaokun Zhang, Yi Dong, Jieyu Zhang, Jan Kautz, Bryan Catanzaro, Andrew Tao, Qingyun Wu, Zhiding Yu, Guilin Liu

CoRR, May, 2025

Dedicated Feedback and Edit Models Empower Inference-Time Scaling for Open-Ended General-Domain Tasks.

Zhilin Wang, Jiaqi Zeng, Olivier Delalleau, Daniel Egert, Ellie Evans, Hoo-Chang Shin, Felipe Soares, Yi Dong, Oleksii Kuchaiev

CoRR, March, 2025

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment.

Shengyang Sun, Yian Zhang, Alexander Bukharin, David Mosallanezhad, Jiaqi Zeng, Soumye Singhal, Gerald Shen, Adithya Renduchintala, Tugrul Konuk, Yi Dong, Zhilin Wang, Dmitry Chichkov, Olivier Delalleau, Oleksii Kuchaiev

CoRR, February, 2025

Diverging Preferences: When do Annotators Disagree and do Models Know?

Michael J. Q. Zhang, Zhilin Wang, Jena D. Hwang, Yi Dong, Olivier Delalleau, Yejin Choi, Eunsol Choi, Xiang Ren, Valentina Pyatkin

Proceedings of the Forty-second International Conference on Machine Learning, 2025

HelpSteer2-Preference: Complementing Ratings with Preferences.

Zhilin Wang, Alexander Bukharin, Olivier Delalleau, Daniel Egert, Gerald Shen, Jiaqi Zeng, Oleksii Kuchaiev, Yi Dong

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

HelpSteer3: Human-Annotated Feedback and Edit Data to Empower Inference-Time Scaling in Open-Ended General-Domain Tasks.

Zhilin Wang, Jiaqi Zeng, Olivier Delalleau, Daniel Egert, Ellie Evans, Hoo-Chang Shin, Felipe Soares, Yi Dong, Oleksii Kuchaiev

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

HelpSteer2: Open-source dataset for training top-performing reward models.

Zhilin Wang, Yi Dong, Olivier Delalleau, Jiaqi Zeng, Gerald Shen, Daniel Egert, Jimmy J. Zhang, Makesh Narsimhan Sreedhar, Oleksii Kuchaiev

CoRR, 2024

NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment.

Gerald Shen, Zhilin Wang, Olivier Delalleau, Jiaqi Zeng, Yi Dong, Daniel Egert, Shengyang Sun, Jimmy J. Zhang, Sahil Jain, Ali Taghibakhshi, Markel Sanz Ausin, Ashwath Aithal, Oleksii Kuchaiev

CoRR, 2024

HelpSteer 2: Open-source dataset for training top-performing reward models.

Zhilin Wang, Yi Dong, Olivier Delalleau, Jiaqi Zeng, Gerald Shen, Daniel Egert, Jimmy Zhang, Makesh Narsimhan Sreedhar, Oleksii Kuchaiev

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM.

Zhilin Wang, Yi Dong, Jiaqi Zeng, Virginia Adams, Makesh Narsimhan Sreedhar, Daniel Egert, Olivier Delalleau, Jane Polak Scowcroft, Neel Kant, Aidan Swope, Oleksii Kuchaiev

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

2023

Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study.

Boxin Wang, Wei Ping, Peng Xu, Lawrence McAfee, Zihan Liu, Mohammad Shoeybi, Yi Dong, Oleksii Kuchaiev, Bo Li, Chaowei Xiao, Anima Anandkumar, Bryan Catanzaro

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF.

Yi Dong, Zhilin Wang, Makesh Narsimhan Sreedhar, Xianchao Wu, Oleksii Kuchaiev

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023