Table-based Fact Verification
9 papers with code • 1 benchmarks • 2 datasets
Verifying facts given semi-structured data.
Benchmarks
These leaderboards are used to track progress in Table-based Fact Verification
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
TabFact
InfoTabS
Most implemented papers
TAPEX: Table Pre-training via Learning a Neural SQL Executor
microsoft/Table-Pretraining
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ICLR 2022
TAPEX addresses the data scarcity challenge via guiding the language model to mimic a SQL executor on the diverse, large-scale and high-quality synthetic corpus.
TabFact: A Large-scale Dataset for Table-based Fact Verification
wenhuchen/Table-Fact-Checking
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ICLR 2020
To this end, we construct a large-scale dataset called TabFact with 16k Wikipedia tables as the evidence for 118k human-annotated natural language statements, which are labeled as either ENTAILED or REFUTED.
Understanding tables with intermediate pre-training
google-research/tapas
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Findings of the Association for Computational Linguistics 2020
To be able to use long examples as input of BERT models, we evaluate table pruning techniques as a pre-processing step to drastically improve the training and prediction efficiency at a moderate drop in accuracy.
AttesTable at SemEval-2021 Task 9: Extending Statement Verification with Tables for Unknown Class, and Semantic Evidence Finding
This paper describes our approach for Task 9 of SemEval 2021: Statement Verification and Evidence Finding with Tables.
Table-based Fact Verification with Salience-aware Learning
From one perspective, our system conducts masked salient token prediction to enhance the model for alignment and reasoning between the table and the statement.
Logic-level Evidence Retrieval and Graph-based Verification Network for Table-based Fact Verification
Specifically, we first retrieve logic-level program-like evidence from the given table and statement as supplementary evidence for the table.
Exploring Decomposition for Table-based Fact Verification
arielsho/decomposition-table-reasoning
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Findings (EMNLP) 2021
Fact verification based on structured data is challenging as it requires models to understand both natural language and symbolic operations performed over tables.
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models
Structured knowledge grounding (SKG) leverages structured knowledge to complete user requests, such as semantic parsing over databases and question answering over knowledge bases.
Table-based Fact Verification with Self-adaptive Mixture of Experts
thumlp/samoe
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Findings (ACL) 2022
The table-based fact verification task has recently gained widespread attention and yet remains to be a very challenging problem.
