2 papers
cs.CV2026
ENTRAP-VL: A Taxonomic Probe for Dual Contextual Entrainment in Vision-Language Models
Karan Goyal, Afreen Hossain, Debojyoti Das +1
Contextual entrainment is the tendency of a model to let auxiliary context in its input pull its output, independently of whether that context is relevant, true, or even meaningful…
cs.AI2026
Mechanistically Interpreting Compression in Vision-Language Models
Veeraraju Elluru, Arth Singh, Roberto Aguero +3
Compressed vision-language models (VLMs) are widely used to reduce memory and compute costs, making them a suitable choice for real-world deployment. However, compressing these mod…