Table Reasoning

Table reasoning focuses on enabling computers to understand and answer questions based on information presented in tabular data. Current research heavily utilizes large language models (LLMs), exploring various prompting strategies, data representations (including image-based tables), and methods to improve their reasoning capabilities, such as knowledge distillation and pre-training with synthetic reasoning examples. This field is significant because it improves information access and automation for tasks involving structured data analysis, impacting diverse applications from question answering systems to scientific data interpretation.