InCoder: A Generative Model for Code Infilling and Synthesis
Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, Mike Lewis
People
Mike Lewis
Research Scientist
I am a Research Scientist at Meta AI Research in Menlo Park working on natural language processing. Previously I was a postdoc at the University of Washington, working with Luke Zettlemoyer on search based structured prediction. I completed my PhD at the University of Edinburgh (advised by Mark Steedman) based on combining distributional and logical approaches to semantics. I have a Masters degree from the University of Oxford, and won a Best Paper award at EMNLP 2016.
Interests
Natural language processing, structured prediction, semantics, parsing, deep learning
Latest Publications
arXiv - 2022
Pre-training via Paraphrasing
Mike Lewis, Marjan Ghazvininejad, Gargi Ghosh, Armen Aghajanyan, Sida Wang, Luke Zettlemoyer
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe Kiela
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, Luke Zettlemoyer
Generalization through Memorization: Nearest Neighbor Language Models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis
Hierarchical Decision Making by Generating and Following Natural Language Instructions
Hengyuan Hu, Denis Yarats, Qucheng Gong, Yuandong Tian, Mike Lewis
