Spremljaj
Kensen Shi
Kensen Shi
Google
Preverjeni e-poštni naslov na google.com
Naslov
Navedeno
Navedeno
Leto
PaLM: Scaling Language Modeling with Pathways
A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ...
Journal of Machine Learning Research 24 (240), 1-113, 2023
57232023
Learning and Evaluating Contextual Embedding of Source Code
A Kanade, P Maniatis, G Balakrishnan, K Shi
International Conference on Machine Learning, 5110-5121, 2020
4862020
Can large language models reason about program invariants?
K Pei, D Bieber, K Shi, C Sutton, P Yin
International Conference on Machine Learning, 27496-27520, 2023
792023
FrAngel: component-based synthesis with control structures
K Shi, J Steinhardt, P Liang
Proceedings of the ACM on Programming Languages 3 (POPL), 73, 2019
672019
BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration
A Odena, K Shi, D Bieber, R Singh, C Sutton, H Dai
International Conference on Learning Representations, 2021
602021
Natural language to code generation in interactive data science notebooks
P Yin, WD Li, K Xiao, A Rao, Y Wen, K Shi, J Howland, P Bailey, ...
arXiv preprint arXiv:2212.09248, 2022
592022
Spark PRM: Using RRTs within PRMs to efficiently explore narrow passages
K Shi, J Denny, NM Amato
2014 IEEE International Conference on Robotics and Automation (ICRA), 4659-4666, 2014
572014
TF-Coder: Program synthesis for tensor manipulations
K Shi, D Bieber, R Singh
ACM Transactions on Programming Languages and Systems (TOPLAS) 44 (2), 1-36, 2022
482022
Lazy Toggle PRM: A single-query approach to motion planning
J Denny, K Shi, NM Amato
2013 IEEE International Conference on Robotics and Automation, 2407-2414, 2013
442013
CrossBeam: Learning to Search in Bottom-Up Program Synthesis
K Shi, H Dai, K Ellis, C Sutton
International Conference on Learning Representations, 2022
312022
Incremental sampling without replacement for sequence models
K Shi, D Bieber, C Sutton
International Conference on Machine Learning, 8785-8795, 2020
312020
NExT: Teaching Large Language Models to Reason about Code Execution
A Ni, M Allamanis, A Cohan, Y Deng, K Shi, C Sutton, P Yin
arXiv preprint arXiv:2404.14662, 2024
212024
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis
K Shi, J Hong, Y Deng, P Yin, M Zaheer, C Sutton
International Conference on Learning Representations, 2024
172024
Grounding Data Science Code Generation with Input-Output Specifications
Y Wen, P Yin, K Shi, H Michalewski, S Chaudhuri, A Polozov
arXiv preprint arXiv:2402.08073, 2024
10*2024
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas
K Shi, H Dai, WD Li, K Ellis, C Sutton
Conference on Neural Information Processing Systems 37, 2023
82023
Systems and methods for synthesizing code from input and output examples
K Shi, R Singh, DJ Bieber
US Patent 11,256,485, 2022
62022
Compositional Generalization and Decomposition in Neural Program Synthesis
K Shi, J Hong, M Zaheer, P Yin, C Sutton
arXiv preprint arXiv:2204.03758, 2022
52022
A Library for Representing Python Programs as Graphs for Machine Learning
D Bieber, K Shi, P Maniatis, C Sutton, V Hellendoorn, D Johnson, ...
arXiv preprint arXiv:2208.07461, 2022
42022
Natural Language Outlines for Code: Literate Programming in the LLM Era
K Shi, D Altınbüken, S Anand, M Christodorescu, K Grünwedel, ...
arXiv preprint arXiv:2408.04820, 2024
22024
Graph Representations of Python Programs via Source-level Static Analysis
C Sutton, D Johnson, D Tarlow, D Bieber, K Shi, P Maniatis, ...
2022
Sistem trenutno ne more izvesti postopka. Poskusite znova pozneje.
Članki 1–20