Sam Skjonsberg

Allen Institute for Artificial Intelligence
https://codeviking.net
Publications6
h-index4
Citations241
Highly Influential Citations24
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  • Publications
  • Influence
Construction of the Literature Graph in Semantic Scholar
TLDR
This paper reduces literature graph construction into familiar NLP tasks, point out research challenges due to differences from standard formulations of these tasks, and report empirical results for each task.
Augmenting Scientific Papers with Just-in-Time, Position-Sensitive Definitions of Terms and Symbols
TLDR
This work introduces ScholarPhi, an augmented reading interface with four novel features: tooltips that surface position-sensitive definitions from elsewhere in a paper, a filter over the paper that “declutters” it to reveal how the term or symbol is used across the paper, automatic equation diagrams that expose multiple definitions in parallel, and an automatically generated glossary of important terms and symbols.
PAWLS: PDF Annotation With Labels and Structure
TLDR
This paper presents PDF Annotation with Labels and Structure (PAWLS), a new annotation tool designed specifically for the PDF document format, particularly suited for mixed-mode annotation and scenarios in which annotators require extended context to annotate accurately.
SUPP.AI: finding evidence for supplement-drug interactions
TLDR
SUPP.AI is an attempt to close the information gap on dietary supplements by making up-to-date evidence on SDIs more discoverable for researchers, clinicians, and consumers.
Extracting evidence of supplement-drug interactions from literature
TLDR
An automated method for extracting evidence of supplement-drug interactions (SDIs) from scientific text is demonstrated, demonstrating that learning the task of DDI classification transfers successfully to the related problem of SDI classification.
Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text
TLDR
This work proposes models to play Iconary, a collaborative game of drawing and guessing based on Pictionary, that poses a novel challenge for the research community and proposes models that are skillful players and able to employ world knowledge in language models toplay with words unseen during training.