Instruction-guided image editors have become highly capable, yet improving them further still depends on human-edited training pairs or external reward models. Such supervision is costly to obtain and can reward plausible failures: a realistic output may leave the requested change undone or alter content that should be...
Ritesh Thawkar, Shubham Patle, Shravan Venkatraman et al.· 0 citations
Magnetic Resonance Imaging (MRI) interpretation is fundamental to clinical decision-making, requiring radiologists to integrate multi-view anatomical planes across sequential timepoints while precisely localizing interval changes. However, existing vision-language benchmarks remain confined to single-timepoint, single-...
Wafa Al Ghallabi, Ritesh Thawkar, Sara Ghaboura et al.· 0 citations
This work introduces CVPD (Contrastive Counterfactual Visual Process Distillation), which is the first fully self-contained framework for dense, on-policy, token-level visual self-distillation for MLLMs, and proposes a three-gate Counterfactual Criterion that identifies visual blind spots where zooming into a region ch...
Shravan Venkatraman, Omkar Thawakar, Ritesh Thawkar et al.· 2 citations
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