565 citations · 2.3k across the 68 of their papers we have counts for
7 papers · 1 filter
QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships
Oyvind Tafjord, Peter Clark, Matt Gardner +2
Many natural language questions require recognizing and reasoning with qualitative relationships (e.g., in science, economics, and medicine), but are challenging to answer with cor…
Exploiting Explicit Paths for Multi-hop Reading Comprehension
Souvik Kundu, Tushar Khot, Ashish Sabharwal +1
We propose a novel, path-based reasoning approach for the multi-hop reading comprehension task where a system needs to combine facts from multiple passages to answer a question. Al…
Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering
Todor Mihaylov, Peter Clark, Tushar Khot +1
We present a new kind of question answering dataset, OpenBookQA, modeled after open book exams for assessing human understanding of a subject. The open book that comes with our que…
Bridging Knowledge Gaps in Neural Entailment via Symbolic Models
Dongyeop Kang, Tushar Khot, Ashish Sabharwal +1
Most textual entailment models focus on lexical gaps between the premise text and the hypothesis, but rarely on knowledge gaps. We focus on filling these knowledge gaps in the Scie…
AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples
Dongyeop Kang, Tushar Khot, Ashish Sabharwal +1
We consider the problem of learning textual entailment models with limited supervision (5K-10K training examples), and present two complementary approaches for it. First, we propos…
Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Peter Clark, Isaac Cowhey, Oren Etzioni +4
We present a new question set, text corpus, and baselines assembled to encourage AI research in advanced question answering. Together, these constitute the AI2 Reasoning Challenge…