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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…