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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…
cs.AI2026
Fluid Reasoning Representations
Dmitrii Kharlapenko, Alessandro Stolfo, Terry Jingchen Zhang +4
Frontier large language models increasingly solve complex tasks involving abstract concepts through extended test-time thinking. Yet we lack a mechanistic account of how extended t…