Evaluating the Smooth Control of Attribute Intensity in Text Generation with LLMs (2024.findings-acl)
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| Challenge: | Controllable text generation is increasingly tailored to individual preferences. |
| Approach: | They propose to evaluate the attribute intensity of text generated by large language models on five different attributes for error, variation of the generated sentence's intensities and relevance to the generation questions. |
| Outcome: | The proposed methods are based on Elo rating system and GPT4 and are able to be trained without training. |
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