Chain-of-Table
Reasoning chain for table understanding
CommonProductProductivityArtificial IntelligenceTable Understanding
Chain-of-Table is a reasoning chain framework for table understanding, specifically designed for tasks such as question answering based on tables and fact verification. It uses tabular data as part of the reasoning chain and guides large language models to perform operation generation and table updates in a contextual learning manner, forming a continuous reasoning chain that demonstrates the reasoning process for given table questions. This reasoning chain contains structured information about intermediate results, enabling more accurate and reliable predictions. Chain-of-Table has achieved new state-of-the-art performance on multiple benchmark tests, including WikiTQ, FeTaQA, and TabFact.
Chain-of-Table Visit Over Time
Monthly Visits
25537072
Bounce Rate
44.24%
Page per Visit
5.9
Visit Duration
00:04:47