1 citations · 1 across the 10 of their papers we have counts for
15 papers
CineMR: Tool-Integrated Vision-Language Reasoning for Quantitative Cardiac MRI Assessment
Kunyang Li, Hai Nguyen, Joshua Lowe +7
Cardiovascular magnetic resonance (CMR), including cine imaging, is a reference standard for the noninvasive assessment of cardiac morphology and ventricular function. Cine CMR int…
On the Limitations of Cross-Lingual Consistency in Multilingual Text-to-image Generation
Sicheng Zhang, Zhonghao Yan, Binzhu Xie +4
Text-to-image (T2I) generation has achieved remarkable progress in recent years. However, existing research has largely focused on English-only settings, leaving cross-lingual perf…
OncoTriad-QA: A Patient-Level Radiology-Pathology-Genomics Benchmark for Pan-Cancer Reasoning
Ahnaf Munir, Dannong Wang, Michael W. McDonald +3
Cancer diagnosis and characterization require integrating complementary evidence from radiology, pathology, genomics, and clinical metadata. However, most medical large language mo…
ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP
Sicheng Zhang, Muzammal Naseer, Binzhu Xie +5
CLIP and its variants are widely adopted visual backbones in multimodal systems, but their pretraining remains dominated by descriptive image-text alignment. As downstream applicat…
TIGeR: A Unified Framework for Time, Images and Geo-location Retrieval
David G. Shatwell, Sirnam Swetha, Mubarak Shah
Many real-world applications in digital forensics, urban monitoring, and environmental analysis require jointly reasoning about visual appearance, location, and time. Beyond standa…
StretchySnake: Flexible SSM Training Unlocks Action Recognition Across Spatio-Temporal Scales
Nyle Siddiqui, Rohit Gupta, Sirnam Swetha +1
State space models (SSMs) have emerged as a competitive alternative to transformers in various tasks. Their linear complexity and hidden-state recurrence make them particularly att…
Safe-LLaVA: A Privacy-Preserving Vision-Language Dataset and Benchmark for Biometric Safety
Younggun Kim, Sirnam Swetha, Fazil Kagdi +1
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in vision-language tasks. However, these models often infer and reveal sensitive biometric attrib…
Cross-View Open-Vocabulary Object Detection in Aerial Imagery
Jyoti Kini, Rohit Gupta, Mubarak Shah
Traditional object detection models are typically trained on a fixed set of classes, limiting their flexibility and making it costly to incorporate new categories. Open-vocabulary…
The Telephone Game: Evaluating Semantic Drift in Unified Models
Sabbir Mollah, Rohit Gupta, Sirnam Swetha +3
Unified models (UMs) combine visual understanding (I2T) and generation (T2I) in a single framework. We focus on T2I and I2T, where cross-consistency---what a model understands, it…
GT-Loc: Unifying When and Where in Images Through a Joint Embedding Space
David G. Shatwell, Ishan Rajendrakumar Dave, Sirnam Swetha +1
Timestamp prediction aims to determine when an image was captured using only visual information, supporting applications such as metadata correction, retrieval, and digital forensi…
HumaniBench: A Human-Centric Framework for Large Multimodal Models Evaluation
Shaina Raza, Aravind Narayanan, Vahid Reza Khazaie +6
Although recent large multimodal models (LMMs) show impressive progress on vision language tasks, their alignment with human centered (HC) principles such as fairness, ethics, incl…
VLDBench Evaluating Multimodal Disinformation with Regulatory Alignment
Shaina Raza, Ashmal Vayani, Aditya Jain +8
Detecting disinformation that blends manipulated text and images has become increasingly challenging, as AI tools make synthetic content easy to generate and disseminate. While mos…
BBQ-V: Benchmarking Visual Stereotype Bias in Large Multimodal Models
Vishal Narnaware, Ashmal Vayani, Rohit Gupta +2
Stereotype biases in Large Multimodal Models (LMMs) perpetuate harmful societal prejudices, undermining the fairness and equity of AI applications. As LMMs grow increasingly influe…
TimeLogic: A Temporal Logic Benchmark for Video QA
Sirnam Swetha, Hilde Kuehne, Mubarak Shah
Temporal logical understanding, a core facet of human cognition, plays a pivotal role in capturing complex sequential events and their temporal relationships within videos. This ca…
X-Former: Unifying Contrastive and Reconstruction Learning for MLLMs
Sirnam Swetha, Jinyu Yang, Tal Neiman +5
Recent advancements in Multimodal Large Language Models (MLLMs) have revolutionized the field of vision-language understanding by integrating visual perception capabilities into La…