2 citations · 2 across the 11 of their papers we have counts for
6 papers · 1 filter
Background Gradients Shape Memorization in Flow Matching
Xuanhua Yin, Boyu Wei, Shuyi Zhang +3
Repetition is closely associated with memorization in generative models, but how other training images affect the retention and copying of targets remains unclear. We study this qu…
ReAL: Accelerating Flow Matching through Segment Advancement with Shared Lookahead
Xuanhua Yin, Chuanzhi Xu, Haoxian Zhou +2
Flow-matching models generate high-quality images and videos, but repeated neural network evaluations make sampling expensive. Skipping evaluations reduces this cost by extending a…
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…
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…
Step-Level Preference Learning for Generative Agents in Social Simulations
Wenchang Gao, Pingyue Sheng, Lanlan Qiu +7
Large language model (LLM)-based generative agents simulate human behavior through long-horizon decision-making processes that comprise intermediate steps such as planning, memory…
LLM Nepotism in Organizational Governance
Shunqi Mao, Wei Guo, Dingxin Zhang +2
Large language models are increasingly used to support organizational decisions from hiring to governance, raising fairness concerns in AI-assisted evaluation. Prior work has focus…