56 citations · 167 across the 15 of their papers we have counts for
23 papers · 1 filter
Generating Sequences by Learning to Self-Correct
Sean Welleck, Ximing Lu, Peter West +4
Sequence generation applications require satisfying semantic constraints, such as ensuring that programs are correct, using certain keywords, or avoiding undesirable content. Langu…
UnifiedQA-v2: Stronger Generalization via Broader Cross-Format Training
Daniel Khashabi, Yeganeh Kordi, Hannaneh Hajishirzi
We present UnifiedQA-v2, a QA model built with the same process as UnifiedQA, except that it utilizes more supervision -- roughly 3x the number of datasets used for UnifiedQA. This…
Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions?
Jieyu Zhao, Daniel Khashabi, Tushar Khot +2
Is it possible to use natural language to intervene in a model's behavior and alter its prediction in a desired way? We investigate the effectiveness of natural language interventi…
GooAQ: Open Question Answering with Diverse Answer Types
Daniel Khashabi, Amos Ng, Tushar Khot +3
While day-to-day questions come with a variety of answer types, the current question-answering (QA) literature has failed to adequately address the answer diversity of questions. T…
Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge
Sumithra Bhakthavatsalam, Daniel Khashabi, Tushar Khot +6
We present the ARC-DA dataset, a direct-answer ("open response", "freeform") version of the ARC (AI2 Reasoning Challenge) multiple-choice dataset. While ARC has been influential in…
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies
Mor Geva, Daniel Khashabi, Elad Segal +3
A key limitation in current datasets for multi-hop reasoning is that the required steps for answering the question are mentioned in it explicitly. In this work, we introduce Strate…