23 citations · 66 across the 22 of their papers we have counts for
4 papers · 1 filter
What Does My QA Model Know? Devising Controlled Probes using Expert Knowledge
Kyle Richardson, Ashish Sabharwal
Open-domain question answering (QA) is known to involve several underlying knowledge and reasoning challenges, but are models actually learning such knowledge when trained on bench…
MonaLog: a Lightweight System for Natural Language Inference Based on Monotonicity
Hai Hu, Qi Chen, Kyle Richardson +3
We present a new logic-based inference engine for natural language inference (NLI) called MonaLog, which is based on natural logic and the monotonicity calculus. In contrast to exi…
Probing Natural Language Inference Models through Semantic Fragments
Kyle Richardson, Hai Hu, Lawrence S. Moss +1
Do state-of-the-art models for language understanding already have, or can they easily learn, abilities such as boolean coordination, quantification, conditionals, comparatives, an…
From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project
Peter Clark, Oren Etzioni, Daniel Khashabi +11
AI has achieved remarkable mastery over games such as Chess, Go, and Poker, and even Jeopardy, but the rich variety of standardized exams has remained a landmark challenge. Even in…