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cs.CV2026
Do Instance Priors Help Weakly Supervised Semantic Segmentation?
Anurag Das, Anna Kukleva, Xinting Hu +2
Semantic segmentation requires dense pixel-level annotations, which are costly and time-consuming to acquire. To address this, we present SeSAM, a framework that uses a foundationa…
cs.CV2026
ClipTTT: CLIP-Guided Test-Time Training Helps LVLMs See Better
Mriganka Nath, Anurag Das, Jiahao Xie +1
Large vision-language models (LVLMs) tend to hallucinate, especially when visual inputs are corrupted at test time. We show that such corruptions act as additional distribution shi…
cs.CV2026
More Images, More Problems? A Controlled Analysis of VLM Failure Modes
Anurag Das, Adrian Bulat, Alberto Baldrati +4
Large Vision Language Models (LVLMs) have demonstrated remarkable capabilities, yet their proficiency in understanding and reasoning over multiple images remains largely unexplored…