Papers with preference-based evaluation

1 papers
Dissecting Human and LLM Preferences (2024.acl-long)

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Challenge: a recent study shows that human and Large Language Model preferences are important for model fine-tuning and evaluation.
Approach: They dissect the preferences of human and 32 different Large Language Models to understand their quantitative composition.
Outcome: The proposed model is compared with 32 different large language models using real-world user-model conversations.

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