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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