Research

Currently interested in using analogical reasoning and other inductive biases for agent memory systems. Additional interests include studying environment feedback and interaction in LLM tool use

Papers

• Learning Extrapolative Sequence Transformations from Markov Chains
  Sophia Hager, Aleem Khan, Andrew Wang, Nicholas Andrews
  ICLR submission, 2024

• RATIONALYST: Pre-training Process-Supervision for Improving Reasoning
  Dongwei Jiang, Guoxuan Wang, Yining Lu, Andrew Wang, Jingyu Zhang, Chuyu Liu, Benjamin Van Durme, Daniel Khashabi
  Arxiv preprint, 2024

• AnaloBench: Benchmarking the Identification of Abstract and Long-context Analogies
  Xiao Ye,* Andrew Wang,* Jacob Choi, Yining Lu, Shreya Sharma, Lingfeng Shen, Vijay Tiyyala, Nicholas Andrews, Daniel Khashabi
  EMNLP (main), 2024

• Learning to Generate Text in Arbitrary Writing Styles
  Aleem Khan, Andrew Wang, Sophia Hager, Nicholas Andrews
  Arxiv preprint, 2023

• Can Authorship Representation Learning Capture Stylistic Features?
  Andrew Wang,* Cristina Aggazzotti,* Rebecca Kotula, Rafael Rivera-Soto, Marcus Bishop, and Nicholas Andrews
  TACL, 2023

* equal contribution

Talks

• 2024 JSALT (Annual Frederick Jelinek Memorial Summer Workshop)
  AnaloBench: Benchmarking the Identification of Abstract and Long-context Analogies

• EMNLP 2023
  Can Authorship Representation Learning Capture Stylistic Features?

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