Tree-of-Text guides LLMs through a three-stage tree process of planning operations on input tables, executing them on sub-tables, and merging short texts into full sports reports, outperforming baselines on ShuttleSet+, RotoWire-FG, and MLB while using 40% of the time and cost of Chain-of-Table.
IEEE Transactions on Knowledge and Data Engi- neering, 36(4):1431–1449
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Tree-of-Text: A Tree-based Prompting Framework for Table-to-Text Generation in the Sports Domain
Tree-of-Text guides LLMs through a three-stage tree process of planning operations on input tables, executing them on sub-tables, and merging short texts into full sports reports, outperforming baselines on ShuttleSet+, RotoWire-FG, and MLB while using 40% of the time and cost of Chain-of-Table.