Maxwell I. Nye

According to our database, Maxwell I. Nye authored at least 16 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Language Modeling with Latent Situations.

Belinda Z. Li, Maxwell I. Nye, Jacob Andreas

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Communicating Natural Programs to Humans and Machines.

Samuel Acquaviva, Yewen Pu, Marta Kryven, Theodoros Sechopoulos, Catherine Wong, Gabrielle E. Ecanow, Maxwell I. Nye, Michael Henry Tessler, Josh Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Show Your Work: Scratchpads for Intermediate Computation with Language Models.

Maxwell I. Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, Charles Sutton, Augustus Odena

CoRR, 2021

Program Synthesis with Large Language Models.

Jacob Austin, Augustus Odena, Maxwell I. Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie J. Cai, Michael Terry, Quoc V. Le, Charles Sutton

CoRR, 2021

DreamCoder: bootstrapping inductive program synthesis with wake-sleep library learning.

Kevin Ellis, Catherine Wong, Maxwell I. Nye, Mathias Sablé-Meyer, Lucas Morales, Luke B. Hewitt, Luc Cary, Armando Solar-Lezama, Joshua B. Tenenbaum

Proceedings of the PLDI '21: 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2021

Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning.

Maxwell I. Nye, Michael Henry Tessler, Joshua B. Tenenbaum, Brenden M. Lake

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A large-scale benchmark for few-shot program induction and synthesis.

Ferran Alet, Javier Lopez-Contreras, James Koppel, Maxwell I. Nye, Armando Solar-Lezama, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Joshua B. Tenenbaum

Proceedings of the 38th International Conference on Machine Learning, 2021

Representing Partial Programs with Blended Abstract Semantics.

Maxwell I. Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B. Tenenbaum, Armando Solar-Lezama

Proceedings of the 9th International Conference on Learning Representations, 2021

LARC: Language annotated Abstraction and Reasoning Corpus.

Samuel Acquaviva, Yewen Pu, Maxwell I. Nye, Catherine Wong, Michael Henry Tessler, Josh Tenenbaum

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

Implicit Representations of Meaning in Neural Language Models.

Belinda Z. Li, Maxwell I. Nye, Jacob Andreas

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning.

Kevin Ellis, Catherine Wong, Maxwell I. Nye, Mathias Sablé-Meyer, Luc Cary, Lucas Morales, Luke B. Hewitt, Armando Solar-Lezama, Joshua B. Tenenbaum

CoRR, 2020

Learning Compositional Rules via Neural Program Synthesis.

Maxwell I. Nye, Armando Solar-Lezama, Josh Tenenbaum, Brenden M. Lake

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Write, Execute, Assess: Program Synthesis with a REPL.

Kevin Ellis, Maxwell I. Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, Armando Solar-Lezama

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning to Infer Program Sketches.

Maxwell I. Nye, Luke B. Hewitt, Joshua B. Tenenbaum, Armando Solar-Lezama

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

The Variational Homoencoder: Learning to learn high capacity generative models from few examples.

Luke B. Hewitt, Maxwell I. Nye, Andreea Gane, Tommi S. Jaakkola, Joshua B. Tenenbaum

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Are Efficient Deep Representations Learnable?

Maxwell I. Nye, Andrew Saxe

Proceedings of the 6th International Conference on Learning Representations, 2018