8 citations · 8 across the 9 of their papers we have counts for
6 papers · 1 filter
How Good are Foundation Models in Longitudinal MRI Disease Progression Reasoning?
Wafa Al Ghallabi, Ritesh Thawkar, Sara Ghaboura +6
Magnetic Resonance Imaging (MRI) interpretation is fundamental to clinical decision-making, requiring radiologists to integrate multi-view anatomical planes across sequential timep…
Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM
Amol Harsh, Zongyan Han, Jean Lahoud +5
Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to the referred 3D region, whil…
Ask, Solve, Generate: Self-Evolving Unified Multimodal Understanding and Generation via Self-Consistency Rewards
Ritesh Thawkar, Shravan Venkatraman, Omkar Thawakar +5
Most unified large multimodal models (LMMs) that support both visual understanding and image generation still rely on curated post-training supervision, such as human annotations,…
Paying More Attention to Visual Tokens in Self-Evolving Large Multimodal Models
Shravan Venkatraman, Ritesh Thawkar, Omkar Thawakar +4
Recently, self-evolving large multimodal models (LMMs) have received attention for improving visual reasoning in a purely unsupervised setting. However, multi-role self-play and se…
CEPO: RLVR Self-Distillation using Contrastive Evidence Policy Optimization
Ahmed Heakl, Abdelrahman M. Shaker, Youssef Mohamed +4
When a model produces a correct solution under reinforcement learning with verifiable rewards (RLVR), every token receives the same reward signal regardless of whether it was a dec…
Mobile-O: Unified Multimodal Understanding and Generation on Mobile Device
Abdelrahman Shaker, Ahmed Heakl, Jaseel Muhammad +8
Unified multimodal models can both understand and generate visual content within a single architecture. Existing models, however, remain data-hungry and too heavy for deployment on…