activity
20132026
most citedLearning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors

60 citations · 302 across the 41 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CL2019

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

Sewon Min, Danqi Chen, Luke Zettlemoyer +1

We introduce an approach for open-domain question answering (QA) that retrieves and reads a passage graph, where vertices are passages of text and edges represent relationships tha…

cs.CL2019★ 21 cited

MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension

Adam Fisch, Alon Talmor, Robin Jia +3

We present the results of the Machine Reading for Question Answering (MRQA) 2019 shared task on evaluating the generalization capabilities of reading comprehension systems. In this…

cs.CL2019

A Discrete Hard EM Approach for Weakly Supervised Question Answering

Sewon Min, Danqi Chen, Hannaneh Hajishirzi +1

Many question answering (QA) tasks only provide weak supervision for how the answer should be computed. For example, TriviaQA answers are entities that can be mentioned multiple ti…

cs.CL2019

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Yinhan Liu, Myle Ott, Naman Goyal +7

Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging. Training is computationally expensive, often…

cs.CL2019

SpanBERT: Improving Pre-training by Representing and Predicting Spans

Mandar Joshi, Danqi Chen, Yinhan Liu +3

We present SpanBERT, a pre-training method that is designed to better represent and predict spans of text. Our approach extends BERT by (1) masking contiguous random spans, rather…