2.3k citations · 6.5k across the 77 of their papers we have counts for
9 papers · 1 filter
Learning to Summarize Radiology Findings
Yuhao Zhang, Daisy Yi Ding, Tianpei Qian +2
The Impression section of a radiology report summarizes crucial radiology findings in natural language and plays a central role in communicating these findings to physicians. Howev…
Graph Convolution over Pruned Dependency Trees Improves Relation Extraction
Yuhao Zhang, Peng Qi, Christopher D. Manning
Dependency trees help relation extraction models capture long-range relations between words. However, existing dependency-based models either neglect crucial information (e.g., neg…
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Zhilin Yang, Peng Qi, Saizheng Zhang +4
Existing question answering (QA) datasets fail to train QA systems to perform complex reasoning and provide explanations for answers. We introduce HotpotQA, a new dataset with 113k…
Semi-Supervised Sequence Modeling with Cross-View Training
Kevin Clark, Minh-Thang Luong, Christopher D. Manning +1
Unsupervised representation learning algorithms such as word2vec and ELMo improve the accuracy of many supervised NLP models, mainly because they can take advantage of large amount…
Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts
Matthew Lamm, Arun Tejasvi Chaganty, Christopher D. Manning +2
To understand a sentence like "whereas only 10% of White Americans live at or below the poverty line, 28% of African Americans do" it is important not only to identify individual f…
CoQA: A Conversational Question Answering Challenge
Siva Reddy, Danqi Chen, Christopher D. Manning
Humans gather information by engaging in conversations involving a series of interconnected questions and answers. For machines to assist in information gathering, it is therefore…