584 citations · 1.3k across the 49 of their papers we have counts for
21 papers · 1 filter
ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of Scientific Concepts
Sonia K. Murthy, Kyle Lo, Daniel King +7
Systems that can automatically define unfamiliar terms hold the promise of improving the accessibility of scientific texts, especially for readers who may lack prerequisite backgro…
Few-shot Mining of Naturally Occurring Inputs and Outputs
Mandar Joshi, Terra Blevins, Mike Lewis +2
Creating labeled natural language training data is expensive and requires significant human effort. We mine input output examples from large corpora using a supervised mining funct…
A Computational Inflection for Scientific Discovery
Tom Hope, Doug Downey, Oren Etzioni +2
We stand at the foot of a significant inflection in the trajectory of scientific discovery. As society continues on its fast-paced digital transformation, so does humankind's colle…
Don't Say What You Don't Know: Improving the Consistency of Abstractive Summarization by Constraining Beam Search
Daniel King, Zejiang Shen, Nishant Subramani +3
Abstractive summarization systems today produce fluent and relevant output, but often "hallucinate" statements not supported by the source text. We analyze the connection between h…
A Search Engine for Discovery of Scientific Challenges and Directions
Dan Lahav, Jon Saad Falcon, Bailey Kuehl +8
Keeping track of scientific challenges, advances and emerging directions is a fundamental part of research. However, researchers face a flood of papers that hinders discovery of im…
VILA: Improving Structured Content Extraction from Scientific PDFs Using Visual Layout Groups
Zejiang Shen, Kyle Lo, Lucy Lu Wang +3
Accurately extracting structured content from PDFs is a critical first step for NLP over scientific papers. Recent work has improved extraction accuracy by incorporating elementary…