Web: http://arxiv.org/abs/2205.05646

May 12, 2022, 1:11 a.m. | Xia Zeng, Arkaitz Zubiaga

cs.LG updates on arXiv.org arxiv.org

As part of an automated fact-checking pipeline, the claim veracity
classification task consists in determining if a claim is supported by an
associated piece of evidence. The complexity of gathering labelled
claim-evidence pairs leads to a scarcity of datasets, particularly when dealing
with new domains. In this paper, we introduce SEED, a novel vector-based method
to few-shot claim veracity classification that aggregates pairwise semantic
differences for claim-evidence pairs. We build on the hypothesis that we can
simulate class representative vectors …

arxiv classification semantic

More from arxiv.org / cs.LG updates on arXiv.org

Data Analyst, Patagonia Action Works

@ Patagonia | Remote

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC