reinforcement learning from human feedback
A family of reinforcement-learning-based training methods that use human judgments, commonly pairwise preferences or ratings, to define or learn a reward signal and then optimize a model or policy using that signal; particular pipelines may also include supervised fine-tuning and a learned reward model.
Metadata
- aliases
- en
- RLHF
- reinforcement learning with human feedback
- concept_id
- reinforcement_learning_from_human_feedback
- preferred
- en
- reinforcement learning from human feedback
- ja
- 人間のフィードバックによる強化学習
- relations
- relations
- broader
- prerequisite
- status
- active