Linyuan Gong

Linyuan Gong

PhD Student in Artificial Intelligence

EECS Department, UC Berkeley

I am a PhD student in Computer Science at University of California, Berkeley, advised by Prof. Alvin Cheung. I was also advised by Prof. Dawn Song at UC Berkeley. Before that, I received my Bachelor’s degree in Computer Science from Peking University, China, advised by Prof. Liwei Wang and Prof. Di He.

I specialize in Artificial Intelligence (AI) with a focus on Large Language Models (LLMs). My research includes pretraining, prompting, and evaluation methodologies for a variety of language models, including BERT, T5, and GPT-like LLMs. My recent research delves into leveraging LLMs for code generation, infilling, transpilation, and understanding, pushing the boundaries of how AI interacts with programming languages.

  • Artificial Intelligence
  • Natural Language Processing
  • Large Language Models
  • Ph.D. in Computer Science, 2020 - Present

    University of California, Berkeley

  • B.S. in Computer Science, 2016 - 2020

    Peking University, Beijing, China

Recent Publications

(2023). ADELT: Transpilation Between Deep Learning Frameworks.

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(2022). Joint Language Semantic and Structure Embedding for Knowledge Graph Completion. In COLING 2022.

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(2021). PlotCoder: Hierarchical Decoding for Synthesizing Visualization Code in Programmatic Context. In ACL 2021.

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(2021). Anytime Sampling for Autoregressive Models via Ordered Autoencoding. In ICLR 2021.

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(2020). Improved Clinical Abbreviation Expansion via Non-Sense-Based Approaches. In ML4H (NeurIPS Workshop) 2020.

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(2020). MC-BERT: Efficient Language Pre-Training via a Meta Controller.

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(2019). Microsoft Research Asia's Systems for WMT19. In WMT19 (ACL 2019 Workshop).


(2019). Efficient training of BERT by progressively stacking. In ICML 2019.

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