Table-based Fact Verification
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Benchmarks
TabFact
Most implemented
Binding Language Models in Symbolic Languages
TAPEX: Table Pre-training via Learning a Neural SQL Executor
Papers
ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics
This paper presents the Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics (ARTEMIS-DA), a novel framework designed to augment Large Language Models (LLMs) for solving complex…
Code GenerationInformation RetrievalQuestion AnsweringRetrieval+3TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoning
Current Large Language Models (LLMs) exhibit limited ability to understand table structures and to apply precise numerical reasoning, which is crucial for tasks such as table question answering (TQA) and table-based fact…
Fact VerificationQuestion AnsweringTable-based Fact VerificationNormTab: Improving Symbolic Reasoning in LLMs Through Tabular Data Normalization
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in parsing textual data and generating code. However, their performance in tasks involving tabular data, especially those requiring …
Semantic ParsingTable-based Fact VerificationEfficient Prompting for LLM-based Generative Internet of Things
Large language models (LLMs) have demonstrated remarkable capacities on various tasks, and integrating the capacities of LLMs into the Internet of Things (IoT) applications has drawn much research attention recently. Due…
Prompt EngineeringQuestion AnsweringSemantic ParsingTable-based Fact VerificationTabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition
Table reasoning is a challenging task that requires understanding both natural language questions and structured tabular data. Large language models (LLMs) have shown impressive capabilities in natural language understan…
Natural Language UnderstandingQuestion AnsweringSemantic ParsingTable-based Fact Verification+2Are Large Language Models Table-based Fact-Checkers?
Table-based Fact Verification (TFV) aims to extract the entailment relation between statements and structured tables. Existing TFV methods based on small-scaled models suffer from insufficient labeled data and weak zero-…
Fact VerificationIn-Context LearningPrompt EngineeringTable-based Fact Verification