55 citations · 59 across the 6 of their papers we have counts for
7 papers · 1 filter
Synthetic Visual Genome 2: Extracting Large-scale Spatio-Temporal Scene Graphs from Videos
Ziqi Gao, Jieyu Zhang, Wisdom Oluchi Ikezogwo +10
We introduce Synthetic Visual Genome 2 (SVG2), a large-scale panoptic video scene graph dataset. SVG2 contains over 636K videos with 6.6M objects, 52.0M attributes, and 6.7M relati…
When Rubrics Fail: Error Enumeration as Reward in Reference-Free RL Post-Training for Virtual Try-On
Wisdom Ikezogwo, Mehmet Saygin Seyfioglu, Ranjay Krishna +1
Reinforcement learning with verifiable rewards (RLVR) and Rubrics as Rewards (RaR) have driven strong gains in domains with clear correctness signals and even in subjective domains…
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…
Quilt-LLaVA: Visual Instruction Tuning by Extracting Localized Narratives from Open-Source Histopathology Videos
Mehmet Saygin Seyfioglu, Wisdom O. Ikezogwo, Fatemeh Ghezloo +2
Diagnosis in histopathology requires a global whole slide images (WSIs) analysis, requiring pathologists to compound evidence from different WSI patches. The gigapixel scale of WSI…
Quilt-1M: One Million Image-Text Pairs for Histopathology
Wisdom Oluchi Ikezogwo, Mehmet Saygin Seyfioglu, Fatemeh Ghezloo +5
Recent accelerations in multi-modal applications have been made possible with the plethora of image and text data available online. However, the scarcity of analogous data in the m…
Multi-modal Masked Autoencoders Learn Compositional Histopathological Representations
Wisdom Oluchi Ikezogwo, Mehmet Saygin Seyfioglu, Linda Shapiro
Self-supervised learning (SSL) enables learning useful inductive biases through utilizing pretext tasks that require no labels. The unlabeled nature of SSL makes it especially impo…