Kensen Shi
Research Areas
Authored Publications
Sort By
Google
Compositional Generalization and Decomposition in Neural Program Synthesis
Joey Hong
Manzil Zaheer
Deep Learning for Code (DL4C) Workshop at ICLR'22 (2022)
Graph Representations of Python Programs via Source-level Static Analysis
Daniel Johnson
David Bieber
Vincent Josua Hellendoorn
Arxiv (2022)
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery
Sharan Narang
Jacob Devlin
Maarten Bosma
Hyung Won Chung
Sebastian Gehrmann
Parker Schuh
Sasha Tsvyashchenko
Abhishek Rao
Yi Tay
Noam Shazeer
Nan Du
Reiner Pope
James Bradbury
Guy Gur-Ari
Toju Duke
Henryk Michalewski
Xavier Garcia
Liam Fedus
David Luan
Barret Zoph
Ryan Sepassi
David Dohan
Shivani Agrawal
Mark Omernick
Marie Pellat
Aitor Lewkowycz
Erica Moreira
Rewon Child
Oleksandr Polozov
Zongwei Zhou
Brennan Saeta
Michele Catasta
Jason Wei
Kathy Meier-Hellstern
arxiv:2204.02311 (2022)
CrossBeam: Learning to Search in Bottom-Up Program Synthesis
Hanjun Dai
Kevin Ellis
International Conference on Learning Representations (ICLR) (2022) (to appear)
BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration
Augustus Odena
David Bieber
Rishabh Singh
Hanjun Dai
International Conference on Learning Representations (ICLR) (2021)
Learning and Evaluating Contextual Embedding of Source Code
Aditya Kanade
International Conference on Machine Learning (ICML), Vienna, Austria (2020)
Incremental Sampling Without Replacement for Sequence Models
David Bieber
Proceedings of the 37th International Conference on Machine Learning (2020)
