{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/attestable-at-semeval-2021-task-9-extending","title":"AttesTable at SemEval-2021 Task 9: Extending Statement Verification with Tables for Unknown Class, and Semantic Evidence Finding","arxiv_id":null,"date":"2021-08-01","proceeding":"SEMEVAL 2021","authors":["Harshit Varma","Aadish Jain","Pratik Ratadiya","Abhishek Rathi"],"abstract":"This 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.","url_abs":"https://aclanthology.org/2021.semeval-1.182/","url_pdf":"https://aclanthology.org/2021.semeval-1.182.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"attestable-at-semeval-2021-task-9-extending","repo_url":"https://github.com/vCreaTek/attestable-semeval","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"fact-checking","task_name":"Fact Checking"},{"task_slug":"fact-verification","task_name":"Fact Verification"},{"task_slug":"natural-language-inference","task_name":"Natural Language Inference"},{"task_slug":"table-based-fact-verification","task_name":"Table-based Fact Verification"}],"methods":[{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"attention-dropout","method_name":"Attention Dropout"},{"method_slug":"bert","method_name":"BERT"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"distilbert","method_name":"DistilBERT"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"linear-warmup-with-linear-decay","method_name":"Linear Warmup With Linear Decay"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"tapas","method_name":"TAPAS"},{"method_slug":"weight-decay","method_name":"Weight Decay"},{"method_slug":"wordpiece","method_name":"WordPiece"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}