5 papers
Decontextualization: Making Sentences Stand-Alone
Eunsol Choi, Jennimaria Palomaki, Matthew Lamm +3
Models for question answering, dialogue agents, and summarization often interpret the meaning of a sentence in a rich context and use that meaning in a new context. Taking excerpts…
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
Sewon Min, Jordan Boyd-Graber, Chris Alberti +50
We review the EfficientQA competition from NeurIPS 2020. The competition focused on open-domain question answering (QA), where systems take natural language questions as input and…
QED: A Framework and Dataset for Explanations in Question Answering
Matthew Lamm, Jennimaria Palomaki, Chris Alberti +4
A question answering system that in addition to providing an answer provides an explanation of the reasoning that leads to that answer has potential advantages in terms of debuggab…
New Protocols and Negative Results for Textual Entailment Data Collection
Samuel R. Bowman, Jennimaria Palomaki, Livio Baldini Soares +1
Natural language inference (NLI) data has proven useful in benchmarking and, especially, as pretraining data for tasks requiring language understanding. However, the crowdsourcing…
TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages
Jonathan H. Clark, Eunsol Choi, Michael Collins +4
Confidently making progress on multilingual modeling requires challenging, trustworthy evaluations. We present TyDi QA---a question answering dataset covering 11 typologically dive…