30 citations · 71 across the 6 of their papers we have counts for
7 papers
A Paragraph-level Multi-task Learning Model for Scientific Fact-Verification
Xiangci Li, Gully Burns, Nanyun Peng
Even for domain experts, it is a non-trivial task to verify a scientific claim by providing supporting or refuting evidence rationales. The situation worsens as misinformation is p…
MELINDA: A Multimodal Dataset for Biomedical Experiment Method Classification
Te-Lin Wu, Shikhar Singh, Sayan Paul +2
We introduce a new dataset, MELINDA, for Multimodal biomEdicaL experImeNt methoD clAssification. The dataset is collected in a fully automated distant supervision manner, where the…
Scientific Discourse Tagging for Evidence Extraction
Xiangci Li, Gully Burns, Nanyun Peng
Evidence plays a crucial role in any biomedical research narrative, providing justification for some claims and refutation for others. We seek to build models of scientific argumen…
An Investigation into the Pedagogical Features of Documents
Emily Sheng, Prem Natarajan, Jonathan Gordon +1
Characterizing the content of a technical document in terms of its learning utility can be useful for applications related to education, such as generating reading lists from large…
Experiment Segmentation in Scientific Discourse as Clause-level Structured Prediction using Recurrent Neural Networks
Pradeep Dasigi, Gully A. P. C. Burns, Eduard Hovy +1
We propose a deep learning model for identifying structure within experiment narratives in scientific literature. We take a sequence labeling approach to this problem, and label cl…
Towards structured sharing of raw and derived neuroimaging data across existing resources
D. B. Keator, K. Helmer, J. Steffener +7
Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is cu…
An analysis of the abstracts presented at the annual meetings of the Society for Neuroscience from 2001 to 2006
J. M. Lin, J. W. Bohland, P. Andrews +3
We extracted and processed abstract data from the SFN annual meeting abstracts during the period 2001-2006, using techniques and software from natural language processing, database…