Research Interests
Machine Learning and Natural Language Processing in general, including neural-symbolic learning, multi-task learning, dialogue systems, foundation models such as LLMs and diffusion models, and composable ML systems. In particular, interaction and co-evolving mechanisms between neural models and symbolic knowledge bases, as well as principles and methodologies to train AI agents with all kinds of experiences (e.g., data instances, knowledge graphs, reward signals, related tasks, auxiliary models).
Education
- 2021, M.S., Language Technologies Institute, Carnegie Mellon University
Advisor: Eric P. Xing and Zhiting Hu - 2019, B.S., ACM Honors Class at Zhiyuan College, Shanghai Jiao Tong University, China
Advisor: Kai Yu and Lu Chen
Experience
- 2022, Student Researcher, Google Research
Hosts: Yun Zhu, Lijuan Liu, and Jindong (JD) Chen
Publications
- LLM360 K2: Building a 65B 360-Open-Source Large Language Model from Scratch Zhengzhong Liu, Bowen Tan, Hongyi Wang, Willie Neiswanger, Tianhua Tao, Haonan Li, Fajri Koto, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Liqun Ma, Liping Tang, Nikhil Ranjan, Yonghao Zhuang, Guowei He, Renxi Wang, Mingkai Deng, Robin Algayres, Yuanzhi Li, Zhiqiang Shen, Preslav Nakov, Eric Xing Pre-Print [arXiv] [Project Page]
- Crystal: Illuminating LLM Abilities on Language and Code Tianhua Tao, Junbo Li, Bowen Tan, Hongyi Wang, William Marshall, Bhargav M Kanakiya, Joel Hestness, Natalia Vassilieva, Zhiqiang Shen, Eric Xing, Zhengzhong Liu COLM 2024 [arXiv] [Project Page]
- LLM360: Towards Fully Transparent Open-Source LLMs Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Xuguang Ren, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Tim Baldwin, Eric P. Xing COLM 2024 [arXiv] [Twitter] [Project Page]
- RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs Bowen Tan, Yun Zhu, Lijuan Liu, Hongyi Wang, Yonghao Zhuang, Jindong Chen, Eric Xing, Zhiting Hu NAACL 2024, Demo / MLSys Workshop @ NeurIPS 2023 [arXiv] [Code] [Twitter] [Slides] [Demo Video] [Project Page] (Best Demo Paper Runner Up @ NAACL 2024)
- Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer Bowen Tan, Yun Zhu, Lijuan Liu, Eric Xing, Zhiting Hu, Jindong Chen NeurIPS 2023 [arXiv] [Code] [Twitter] [Slides] [Poster] [Google AI Blog] [Model Card]
- Neural-Symbolic Interaction and Co-Evolving Bowen Tan, Shibo Hao, Eric Xing, Zhiting Hu Compendium of Neurosymbolic Artificial Intelligence, IOS Press [EBook]
- BertNet: Harvesting Knowledge Graphs from Pretrained Language Models Bowen Tan*, Shibo Hao*, Kaiwen Tang* (equal contrib.), Bin Ni, Xiyan Shao, Hengzhe Zhang, Eric P Xing, Zhiting Hu ACL 2023, Findings [arXiv] [Code]
- Text Generation with Efficient (Soft) Q-Learning Han Guo, Bowen Tan, Zhengzhong Liu, Eric P Xing, Zhiting Hu EMNLP 2022, Findings [arXiv] [Code]
- Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation Bowen Tan*, Mingkai Deng* (equal contrib.), Zhengzhong Liu, Eric P Xing, Zhiting Hu EMNLP 2021 [arXiv] [Code]
- Progressive Generation of Long Text Bowen Tan, Zichao Yang, Maruan AI-Shedivat, Eric P. Xing, Zhiting Hu NAACL 2021 [arXiv] [Slides] [Code]
- Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach Bowen Tan, Lianhui Qin, Eric Xing and Zhiting Hu EMNLP 2020 [arXiv] [Slides] [Code]
- Learning Data Manipulation for Augmentation and Weighting Bowen Tan*, Zhiting Hu* (equal contrib.), Ruslan Salakhutdinov, Tom Mitchell, Eric P. Xing NeurIPS 2019 [arXiv] [Code]
- Connecting the Dots between MLE and RL for Sequence Generation Bowen Tan*, Zhiting Hu* (equal contrib.), Zichao Yang, Ruslan Salakhutdinov, Eric Xing Pre-print 2019 [arXiv] [Code] [Blog] [Blog (in Chinese)] (Best paper on ICLR2019 drlStructPred workshop)
- Structured Dialogue Policy with Graph Neural Networks Bowen Tan*, Lu Chen* (equal contrib.), Sishan Long, Kai Yu COLING 2018 [arXiv] (selected as "Area Chair Favorites".)
- Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation Zhiting Hu, Haoran Shi, Bowen Tan, Wentao Wang, Zichao Yang, Tiancheng Zhao, Junxian He, Lianhui Qin, Di Wang, Xuezhe Ma, Zhengzhong Liu, Xiaodan Liang, Wangrong Zhu, Devendra Singh Sachan, Eric P. Xing ACL 2019 (demo paper) [arXiv] [slides] [Website] [GitHub (TensorFlow)] [GitHub (PyTorch)] [Blog] [Blog (in Chinese)] (Best demo paper nomination)
- On the Generation of Medical Dialogs for COVID-19 Meng Zhou, Zechen Li, Bowen Tan, Guangtao Zeng, Wenmian Yang, Xuehai He, Zeqian Ju, Subrato Chakravorty, Shu Chen, Xingyi Yang, Yichen Zhang, Qingyang Wu, Zhou Yu, Eric Xing, Pengtao Xie ACL 2021
- AgentGraph: Towards Universal Dialogue Management with Structured Deep Reinforcement Learning Lu Chen, Zhi Chen, Bowen Tan, Sishan Long, Milica Gasic, Kai Yu IEEE/ACM Transactions on Audio, Speech, and Language Processing 2019 [arXiv]
- Schema-Guided Multi-Domain Dialogue State Tracking with Graph Attention Neural Networks Lu Chen, Boer Lv, Chi Wang, Su Zhu, Bowen Tan, Kai Yu AAAI 2020 [arXiv]
- Policy Adaptation for Deep Reinforcement Learning-based Dialogue Management Lu Chen, Cheng Chang, Zhi Chen, Bowen Tan, Milica Gasic, Kai Yu ICASSP 2018 [arXiv]
Awards & Honors (Selected)
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NAACL 2024 Best Demo Paper Runner Up, 2024.
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ACL 2019 Best Demo Paper Nomination, 2019.
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ICLR 2019 drlStructPred Workshop Best Paper, 2019.
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COLING 2018 "Area Chair Favorites", 2018.
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RongChang Scholarship, Shanghai Jiao Tong University, 2017 & 2018.
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Zhiyuan Outstanding Scholarship, Shanghai Jiao Tong University, 2019.
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Zhiyuan Honor Degree of Bachelor, Shanghai Jiao Tong University, 2019.
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Outstanding Graguate, Shanghai Jiao Tong University, 2019.
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Second Runner-up, ACM-ICPC Reginal Nha-Trang, 2016.
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Gold Medal, ACM-ICPC China-Final, 2016.
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Gold Medal, ACM-ICPC Reginal Beijing, 2015.