9 papers · 1 filter
Asking It All: Generating Contextualized Questions for any Semantic Role
Valentina Pyatkin, Paul Roit, Julian Michael +3
Asking questions about a situation is an inherent step towards understanding it. To this end, we introduce the task of role question generation, which, given a predicate mention an…
Prompting Contrastive Explanations for Commonsense Reasoning Tasks
Bhargavi Paranjape, Julian Michael, Marjan Ghazvininejad +2
Many commonsense reasoning NLP tasks involve choosing between one or more possible answers to a question or prompt based on knowledge that is often implicit. Large pretrained langu…
Asking without Telling: Exploring Latent Ontologies in Contextual Representations
Julian Michael, Jan A. Botha, Ian Tenney
The success of pretrained contextual encoders, such as ELMo and BERT, has brought a great deal of interest in what these models learn: do they, without explicit supervision, learn…
AmbigQA: Answering Ambiguous Open-domain Questions
Sewon Min, Julian Michael, Hannaneh Hajishirzi +1
Ambiguity is inherent to open-domain question answering; especially when exploring new topics, it can be difficult to ask questions that have a single, unambiguous answer. In this…
Controlled Crowdsourcing for High-Quality QA-SRL Annotation
Paul Roit, Ayal Klein, Daniela Stepanov +5
Question-answer driven Semantic Role Labeling (QA-SRL) was proposed as an attractive open and natural flavour of SRL, potentially attainable from laymen. Recently, a large-scale cr…
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia +5
In the last year, new models and methods for pretraining and transfer learning have driven striking performance improvements across a range of language understanding tasks. The GLU…