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2021 SEMEVAL SemEval 2021

AttesTable at SemEval-2021 Task 9: Extending Statement Verification with Tables for Unknown Class, and Semantic Evidence Finding

Abstract

AbstractThis paper describes our approach for Task 9 of SemEval 2021: Statement Verification and Evidence Finding with Tables. We participated in both subtasks, namely statement verification and evidence finding. For the subtask of statement verification, we extend the TAPAS model to adapt to the ‘unknown’ class of statements by finetuning it on an augmented version of the task data. For the subtask of evidence finding, we finetune the DistilBERT model in a Siamese setting.

🌉 Interdisciplinary Bridge — Machine Learning and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Harshit Varma , Aadish Jain , Pratik Ratadiya , Abhishek Rathi

Topics

Machine Learning > Core Methods > Classification Natural Language Processing > Applications > Machine Reading Comprehension Natural Language Processing > Resources & Methods > Large Language Models

Keywords

table understanding statement verification siamese network table-based reasoning evidence finding
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