7 citations · 31 across the 43 of their papers we have counts for
9 papers · 2 filters
Mull-Tokens: Modality-Agnostic Latent Thinking
Arijit Ray, Ahmed Abdelkader, Chengzhi Mao +5
Reasoning goes beyond language; the real world requires reasoning about space, time, affordances, and much more that words alone cannot convey. Existing multimodal models exploring…
SIMS-V: Simulated Instruction-Tuning for Spatial Video Understanding
Ellis Brown, Arijit Ray, Ranjay Krishna +3
Despite impressive high-level video comprehension, multimodal language models struggle with spatial reasoning across time and space. While current spatial training approaches rely…
Synthetic Object Compositions for Scalable and Accurate Learning in Detection, Segmentation, and Grounding
Weikai Huang, Jieyu Zhang, Taoyang Jia +5
Visual grouping -- operationalized through tasks such as instance segmentation, visual grounding, and object detection -- enables applications ranging from robotic perception to ph…
Explain Before You Answer: A Survey on Compositional Visual Reasoning
Fucai Ke, Joy Hsu, Zhixi Cai +10
Compositional visual reasoning has emerged as a key research frontier in multimodal AI, aiming to endow machines with the human-like ability to decompose visual scenes, ground inte…
VideoMolmo: Spatio-Temporal Grounding Meets Pointing
Ghazi Shazan Ahmad, Ahmed Heakl, Hanan Gani +4
Spatio-temporal localization is vital for precise interactions across diverse domains, from biological research to autonomous navigation and interactive interfaces. Current video-b…
Unfolding Spatial Cognition: Evaluating Multimodal Models on Visual Simulations
Linjie Li, Mahtab Bigverdi, Jiawei Gu +5
Spatial cognition is essential for human intelligence, enabling problem-solving through visual simulations rather than solely relying on verbal reasoning. However, existing AI benc…
One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory
Chenhao Zheng, Jieyu Zhang, Mohammadreza Salehi +5
Effective video tokenization is critical for scaling transformer models for long videos. Current approaches tokenize videos using space-time patches, leading to excessive tokens an…
PathFinder: A Multi-Modal Multi-Agent System for Medical Diagnostic Decision-Making Applied to Histopathology
Fatemeh Ghezloo, Mehmet Saygin Seyfioglu, Rustin Soraki +6
Diagnosing diseases through histopathology whole slide images (WSIs) is fundamental in modern pathology but is challenged by the gigapixel scale and complexity of WSIs. Trained his…
MedicalNarratives: Connecting Medical Vision and Language with Localized Narratives
Wisdom O. Ikezogwo, Kevin Zhang, Mehmet Saygin Seyfioglu +3
Multi-modal models are data hungry. While datasets with natural images are abundant, medical image datasets can not afford the same luxury. To enable representation learning for me…