Papers with LoFT

1 papers
LoFT: Enhancing Faithfulness and Diversity for Table-to-Text Generation via Logic Form Control (2023.eacl-main)

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Challenge: Existing models for LT2T generation focus on surface-level realizations without much logical inference.
Approach: They propose a model that uses logic forms as fact verifiers and content planners to control LT2T generation.
Outcome: Experimental results show that the proposed model addresses unfaithfulness and diversity issues simultaneously.

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