[LG] Self-Exploring Language Models: Active Preference Elicitation for Online Alignment https://t.co/Guz0zazLzy - Standard RLHF frameworks passively explore by sampling from the trained LLM, which can easily get stuck at local optima and overfit to current data. This paper… https://t.co/VVTuFGu2ij

Marktechpost AI Dev News ⚡@Marktechpost

2 years ago

Advancing Ethical AI: Preference Matching Reinforcement Learning from Human Feedback RLHF for Aligning LLMs with Human Preferences Quick read: https://t.co/wrlNk9zJGa Paper: https://t.co/8AQdVygp2q @weijie444

Preferred-Action-Optimized Diffusion Policies for Offline Reinforcement Learning. https://t.co/6WJhcGzsUt