Boshi Wang (汪博石)

• 10/2024 | Our paper studying grokking in Transformer's implicit reasoning is accepted to NeurIPS-24. See you in Vancouver!

• 05/2024 | Tool learning through simulated trial and error accepted to ACL-24.

• 07/2023 | Our paper on understanding chain-of-thought prompting got an Honorable Mention at ACL-23!

• 05/2023 | Started my internship at Microsoft Semantic Machines.

• 05/2023 | Check out our paper on evaluating LLM's reasoning via debate.

• 05/2023 | Understanding Chain-of-Thought prompting accepted to ACL-23. See you in Toronto!

• 10/2022 | Paper on enhancing multi-step reasoning abilities of pretrained language models accepted to EMNLP-22.

• 08/2021 | Began my PhD @ OSU! Go Buckeyes!

Grokked Transformers are Implicit Reasoners: A Mechanistic Journey to the Edge of Generalization

B. Wang, X. Yue, Y. Su, H. Sun

NeurIPS-24. Short version in the 1st Mechanistic Interpretability Workshop, ICML-24

Paper Code

LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error

B. Wang, H. Fang, J. Eisner, B. Van Durme, Y. Su

ACL-24, The 62nd Annual Meeting of the Association for Computational Linguistics

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Can ChatGPT Defend its Belief in Truth? Evaluting LLM Reasoning via Debate

B. Wang, X. Yue, H. Sun

EMNLP-23 (findings), The 2023 Conference on Empirical Methods in Natural Language Processing

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Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

B. Wang, S. Min, X. Deng, J. Shen, W. You, L. Zettlemoyer, H. Sun

ACL-23 (Honorable Mention), The 61st Annual Meeting of the Association for Computational Linguistics

Paper Code

Mind2Web: Towards a Generalist Agent for the Web

X. Deng, Y. Gu, B. Zheng, S. Chen, S. Stevens, B. Wang, H. Sun, Y. Su

NeurIPS-23 Dataset Track (Spotlight), Thirty-seventh Conference on Neural Information Processing Systems

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Iteratively Prompt Pre-trained Language Models for Chain of Thought

B. Wang, X. Deng, H. Sun

EMNLP-22 (Oral), The 2022 Conference on Empirical Methods in Natural Language Processing

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Homomorphic Sensing: Sparsity and Noise

L. Peng, B. Wang and M. C. Tsakiris

ICML-21, Proceedings of the 38th International Conference on Machine Learning

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Microsoft Semantic Machines

Research Intern

Microsoft Research Asia

Research Intern

Institue of Mathematical Sciences, ShanghaiTech University

Research Assistant