64 citations · 98 across the 11 of their papers we have counts for
5 papers · 1 filter
Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?
Xilun Chen, Kushal Lakhotia, Barlas Oğuz +6
Despite their recent popularity and well-known advantages, dense retrievers still lag behind sparse methods such as BM25 in their ability to reliably match salient phrases and rare…
Decoupled Transformer for Scalable Inference in Open-domain Question Answering
Haytham ElFadeel, Stan Peshterliev
Large transformer models, such as BERT, achieve state-of-the-art results in machine reading comprehension (MRC) for open-domain question answering (QA). However, transformers have…
Robustly Optimized and Distilled Training for Natural Language Understanding
Haytham ElFadeel, Stan Peshterliev
In this paper, we explore multi-task learning (MTL) as a second pretraining step to learn enhanced universal language representation for transformer language models. We use the MTL…
Conversational Answer Generation and Factuality for Reading Comprehension Question-Answering
Stan Peshterliev, Barlas Oguz, Debojeet Chatterjee +2
Question answering (QA) is an important use case on voice assistants. A popular approach to QA is extractive reading comprehension (RC) which finds an answer span in a text passage…
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…