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iTBLS: A Dataset of Interactive Conversations Over Tabular Information
April 22, 2024, 4:42 a.m. | Anirudh Sundar, Christopher Richardson, William Gay, Larry Heck
cs.LG updates on arXiv.org arxiv.org
Abstract: This paper introduces Interactive Tables (iTBLS), a dataset of interactive conversations situated in tables from scientific articles. This dataset is designed to facilitate human-AI collaborative problem-solving through AI-powered multi-task tabular capabilities. In contrast to prior work that models interactions as factoid QA or procedure synthesis, iTBLS broadens the scope of interactions to include mathematical reasoning, natural language manipulation, and expansion of existing tables from natural language conversation by delineating interactions into one of three tasks: …
abstract ai-powered articles arxiv capabilities collaborative contrast conversations cs.ai cs.cl cs.lg dataset human information interactions interactive paper prior problem-solving scientific synthesis tables tabular through type work
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