3 papers
cs.CV2026
Steering Vision-Language Models with Joint Sparse Autoencoders
Huizhen Shu, Xuying Li, Hongxu Lin +2
Sparse Autoencoders (SAEs) have shown promise for analyzing language models, but applying them to vision-language models (VLMs) often yields representations that are difficult to u…
cs.CV2026
PMCE: Probabilistic Multi-Granularity Semantics with Caption-Guided Enhancement for Few-Shot Learning
Jiaying Wu, Can Gao, Jinglu Hu +3
Few-shot learning aims to identify novel categories from only a handful of labeled samples, where prototypes estimated from scarce data are often biased and generalize poorly. Sema…
econ.GN2025
Product Design Using Generative Adversarial Network: Incorporating Consumer Preference and External Data
Hui Li, Jian Ni, Fangzhu Yang
The rise of generative artificial intelligence (AI) has facilitated automated product design but often neglects valuable consumer preference data within companies' internal dataset…