AttesTable at SemEval-2021 Task 9: Extending Statement Verification with Tables for Unknown Class, and Semantic Evidence Finding (2021-01-01T00:00:00.000000Z)

TL;DR

This paper describes the approach for Task 9 of SemEval 2021: Statement Verification and Evidence Finding with Tables, whereby the TAPAS model is extended to adapt to the ‘unknown’ class of statements by finetuning it on an augmented version of the task data.

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.

Authors

Harshit Varma

1 papers

Aadish Jain

1 papers

Pratik Ratadiya

1 papers

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

TL;DR

Abstract

Authors

References23 items

SemEval-2021 Task 9: Fact Verification and Evidence Finding for Tabular Data in Scientific Documents (SEM-TAB-FACTS)

Learn to Combine Linguistic and Symbolic Information for Table-based Fact Verification

Program Enhanced Fact Verification with Verbalization and Graph Attention Network

Understanding tables with intermediate pre-training

Global Table Extractor (GTE): A Framework for Joint Table Identification and Cell Structure Recognition Using Visual Context

TaPas: Weakly Supervised Table Parsing via Pre-training

LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network

An Attention Ensemble Based Approach for Multilabel Profanity Detection

Unsupervised Question Answering for Fact-Checking

Evolution of transfer learning in natural language processing

DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Multilingual Cyber Abuse Detection using Advanced Transformer Architecture

TabFact: A Large-scale Dataset for Table-based Fact Verification

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Decoupled Weight Decay Regularization

Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation

Search-based Neural Structured Learning for Sequential Question Answering

A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

A large annotated corpus for learning natural language inference

Compositional Semantic Parsing on Semi-Structured Tables

Dimensionality Reduction by Learning an Invariant Mapping

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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