3 papers
cs.IR2026
Rethinking Item Tokenization in Generative Recommenders: From Fixed Atoms to Semantic Subwords
Xinrui Miao, Mingjia Yin, Jiaqing Zhang +5
In generative recommender systems, items are typically tokenized into fixed-length semantic ID sequences for autoregressive next-item prediction. However, for user-context modeling…
cs.CV2026
DefaultShift: Auditing Semantic Default Shift in Accelerated Text-to-Image Models
Xuanhua Yin, Chuanzhi Xu, Shunqi Mao +2
Few-step text-to-image models increasingly replace slower generators, yet acceleration can silently change distributions over unspecified attributes even when individual outputs re…
cs.CV2026
Calibrate What You SHIP: Post-Selection Risk Control for Verifier-Guided Text-to-Image Generation
Xuanhua Yin, Shunqi Mao, Wei Guo +2
Verifier-guided text-to-image systems increasingly use test-time search to select, refine, or stop among multiple candidates, yet release thresholds are often calibrated on individ…