80 citations · 159 across the 7 of their papers we have counts for
16 papers · 1 filter
EditEval: An Instruction-Based Benchmark for Text Improvements
Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang +6
Evaluation of text generation to date has primarily focused on content created sequentially, rather than improvements on a piece of text. Writing, however, is naturally an iterativ…
Autoregressive Search Engines: Generating Substrings as Document Identifiers
Michele Bevilacqua, Giuseppe Ottaviano, Patrick Lewis +3
Knowledge-intensive language tasks require NLP systems to both provide the correct answer and retrieve supporting evidence for it in a given corpus. Autoregressive language models…
A Few More Examples May Be Worth Billions of Parameters
Yuval Kirstain, Patrick Lewis, Sebastian Riedel +1
We investigate the dynamics of increasing the number of model parameters versus the number of labeled examples across a wide variety of tasks. Our exploration reveals that while sc…
Domain-matched Pre-training Tasks for Dense Retrieval
Barlas Oğuz, Kushal Lakhotia, Anchit Gupta +8
Pre-training on larger datasets with ever increasing model size is now a proven recipe for increased performance across almost all NLP tasks. A notable exception is information ret…
PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them
Patrick Lewis, Yuxiang Wu, Linqing Liu +5
Open-domain Question Answering models which directly leverage question-answer (QA) pairs, such as closed-book QA (CBQA) models and QA-pair retrievers, show promise in terms of spee…
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…