Semantic Flow Regularization: Teaching LLMs to Generate Diverse Yet Coherent Responses 事件

Semantic Flow Regularization: Teaching LLMs to Generate Diverse Yet Coherent Responses arXiv:2605.27971v1 Announce Type: new Abstract: When large language models are fine-tuned to generate persona- or tone-conditioned responses, their output diversity is severely limited--a failure we term Cross-Style Collapse. We trace this collapse to the cross-entropy objective, which under shared representations tends to suppress diverse continuations. We propose Semantic Flow Regularization (SFR), a lightw