2026
Mitigating Semantic Collapse in Generative Personalization with Test-Time Embedding Adjustment
ICLR 2026poster
In this paper, we investigate the semantic collapsing problem in generative personalization, an under-explored topic where the learned visual concept ($V$) gradually shifts from its original textual meaning and comes to dominate other concepts in multi-concept input prompts. This issue not only redu…