Papers with LMSYS

1 papers
User Feedback in Human-LLM Dialogues: A Lens to Understand Users But Noisy as a Learning Signal (2025.emnlp-main)

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Challenge: a recent study shows that asking for direct user feedback can be disruptive . we examine whether incorporating the contents of user feedback improves model performance .
Approach: They analyze user feedback in the user-LLM conversation logs and harvest learning signals from it.
Outcome: The proposed approach can lead to model degradation on two user-LM interaction datasets.

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