TABFACT
Related Papers
Learn to Combine Linguistic and Symbolic Information for Table-based Fact Verification
AbstractTable-based fact verification is expected to perform both linguistic reasoning and symbolic reasoning. Existing methods lack attention to take advantage of the combination of linguistic information and symbolic information. In …...
Logical Natural Language Generation from Open-Domain Tables
AbstractNeural natural language generation (NLG) models have recently shown remarkable progress in fluency and coherence. However, existing studies on neural NLG are primarily focused on surface-level realizations with limited emphasis …...
Table Fact Verification with Structure-Aware Transformer
AbstractVerifying fact on semi-structured evidence like tables requires the ability to encode structural information and perform symbolic reasoning. Pre-trained language models trained on natural language could not be directly applied …...
Understanding tables with intermediate pre-training
AbstractTable entailment, the binary classification task of finding if a sentence is supported or refuted by the content of a table, requires parsing language and table structure as well as …...
BOUN at SemEval-2021 Task 9: Text Augmentation Techniques for Fact Verification in Tabular Data
AbstractIn this paper, we present our text augmentation based approach for the Table Statement Support Subtask (Phase A) of SemEval-2021 Task 9. We experiment with different text augmentation techniques such …...
Logic-level Evidence Retrieval and Graph-based Verification Network for Table-based Fact Verification
AbstractTable-based fact verification task aims to verify whether the given statement is supported by the given semi-structured table. Symbolic reasoning with logical operations plays a crucial role in this task. …...
Learning to Generate Programs for Table Fact Verification via Structure-Aware Semantic Parsing
AbstractTable fact verification aims to check the correctness of textual statements based on given semi-structured data. Most existing methods are devoted to better comprehending logical operations and tables, but they …...
PASTA: Table-Operations Aware Fact Verification via Sentence-Table Cloze Pre-training
AbstractFact verification has attracted a lot of attention recently, e.g., in journalism, marketing, and policymaking, as misinformation and dis- information can sway one’s opinion and affect one’s actions. While fact-checking …...
Table-based Fact Verification with Self-adaptive Mixture of Experts
AbstractThe table-based fact verification task has recently gained widespread attention and yet remains to be a very challenging problem. It inherently requires informative reasoning over natural language together with different …...
TableFormer: Robust Transformer Modeling for Table-Text Encoding
AbstractUnderstanding tables is an important aspect of natural language understanding. Existing models for table understanding require linearization of the table structure, where row or column order is encoded as an …...
Large Language Models are few(1)-shot Table Reasoners
AbstractRecent literature has shown that large language models (LLMs) are generally excellent few-shot reasoners to solve text reasoning tasks. However, the capability of LLMs on table reasoning tasks is yet …...