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20182026
most citedDreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning

35 citations · 200 across the 11 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.LG2021★ 16 cited

Show Your Work: Scratchpads for Intermediate Computation with Language Models

Maxwell Nye, Anders Johan Andreassen, Guy Gur-Ari +9

Large pre-trained language models perform remarkably well on tasks that can be done "in one pass", such as generating realistic text or synthesizing computer programs. However, the…

cs.PL2021★ 28 cited

Program Synthesis with Large Language Models

Jacob Austin, Augustus Odena, Maxwell Nye +8

This paper explores the limits of the current generation of large language models for program synthesis in general purpose programming languages. We evaluate a collection of such m…

cs.AI2021★ 7 cited

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

Maxwell Nye, Michael Henry Tessler, Joshua B. Tenenbaum +1

Human reasoning can often be understood as an interplay between two systems: the intuitive and associative ("System 1") and the deliberative and logical ("System 2"). Neural sequen…

cs.AI2021

Communicating Natural Programs to Humans and Machines

Samuel Acquaviva, Yewen Pu, Marta Kryven +6

The Abstraction and Reasoning Corpus (ARC) is a set of procedural tasks that tests an agent's ability to flexibly solve novel problems. While most ARC tasks are easy for humans, th…

cs.CL2021

Implicit Representations of Meaning in Neural Language Models

Belinda Z. Li, Maxwell Nye, Jacob Andreas

Does the effectiveness of neural language models derive entirely from accurate modeling of surface word co-occurrence statistics, or do these models represent and reason about the…