Papers with retrieval-augmented modular prompt tuning
Retrieval-Augmented Modular Prompt Tuning for Low-Resource Data-to-Text Generation (2024.lrec-main)
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| Challenge: | Data-to-text generation methods are often limited by data sparsity and lack of training data. |
| Approach: | They propose a retrieval-augmented modular prompt tuning method that generates texts with few hallucinations from structured data inputs. |
| Outcome: | The proposed method generates texts with few hallucinations and achieves state-of-the-art performance on a dataset for drone handover message generation. |