8 citations · 8 across the 3 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2024
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment
Shenao Zhang, Donghan Yu, Hiteshi Sharma +6
Preference optimization, particularly through Reinforcement Learning from Human Feedback (RLHF), has achieved significant success in aligning Large Language Models (LLMs) to adhere…
cs.LG2019
Sample Elicitation
Jiaheng Wei, Zuyue Fu, Yang Liu +3
It is important to collect credible training samples for building data-intensive learning systems (e.g., a deep learning system). Asking people to report complex distributi…