Your Mouse and Eyes Secretly Leak Your Preference: LLM Alignment using Implicit Feedback from Users (opens in new tab)

To align a Large Language Model (LLM), most existing methods collect explicit human feedback and train a reward model to predict the human preference based on the response text. These existing methods have two key limitations. First, the users rarely provide explicit feedback for LLM responses, which makes the high-quality preference annotation expensive to collect. Second, the methods do not leverage implicit human feedback, which has proven vi...