2 papers
cs.CV2026
Don't Settle at the Mode! Mitigating Diversity Collapse in Pretrained Flow Models via Feature Self-Guidance
Pradhaan S Bhat, Rishubh Parihar, Abhijnya Bhat +1
State-of-the-art flow models generate stunning images from text or image prompts. However, they suffer from diversity collapse when generating multiple samples under the same condi…
cs.CV2026
Do Vision Language Models Need to Process Image Tokens?
Sambit Ghosh, R. Venkatesh Babu, Chirag Agarwal
Vision Language Models (VLMs) have achieved remarkable success by integrating visual encoders with large language models (LLMs). While VLMs process dense image tokens across deep t…