Pushmeet Kohli

Summary - TerpreT: A Probabilistic Programming Language for Program Induction

2016 · arXiv (Cornell University)

We study machine learning formulations of inductive program synthesis; that is, given input-output examples, synthesize source code that maps inputs to corresponding outputs. Our key contribution is TerpreT, a domain-specific language for expressing program synthesis …

Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis

2018 · arXiv (Cornell University)

Program synthesis is the task of automatically generating a program consistent with a specification. Recent years have seen proposal of a number of neural approaches for program synthesis, many of which adopt a sequence generation …

Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures

2018 · arXiv (Cornell University)

This paper addresses the problem of evaluating learning systems in safety critical domains such as autonomous driving, where failures can have catastrophic consequences. We focus on two problems: searching for scenarios when learned agents fail …

Analysing Mathematical Reasoning Abilities of Neural Models

2019 · arXiv (Cornell University)

Mathematical reasoning---a core ability within human intelligence---presents some unique challenges as a domain: we do not come to understand and solve mathematical problems primarily on the back of experience and evidence, but on the basis …

A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories

2016

Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, James Allen. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. …