HyperTrace: Hypothesis-Based Preference Tracing for Online LLM Personalization
A new arXiv paper introduces HyperTrace, a training-free method for adapting large language model responses to individual users. The approach targets preferences that are latent and only revealed gradually through interaction, an area where existing techniques based on stored histories or retrieved memories reportedly fall short. The work frames personalization as a preference-tracing problem driven by hypotheses formed during ongoing conversations.