5 papers
OpenMedReason: Scientific Reasoning Supervision for Medical Vision-Language Models
Negin Baghbanzadeh, Pritam Sarkar, Michael Colacci +6
High-stakes clinical use of large vision-language models (LVLMs) requires reasoning that is grounded in visual evidence and clinical knowledge, not just correct final answers. We i…
Self-alignment of Large Video Language Models with Refined Regularized Preference Optimization
Pritam Sarkar, Ali Etemad
Despite recent advances in Large Video Language Models (LVLMs), they still struggle with fine-grained temporal understanding, hallucinate, and often make simple mistakes on even si…
CLARE: Cognitive Load Assessment in REaltime with Multimodal Data
Anubhav Bhatti, Prithila Angkan, Behnam Behinaein +11
We present a novel multimodal dataset for Cognitive Load Assessment in REal-time (CLARE). The dataset contains physiological and gaze data from 24 participants with self-reported c…
VCRBench: Exploring Long-form Causal Reasoning Capabilities of Large Video Language Models
Pritam Sarkar, Ali Etemad
Despite recent advances in video understanding, the capabilities of Large Video Language Models (LVLMs) to perform video-based causal reasoning remains underexplored, largely due t…
Mitigating Object Hallucination in MLLMs via Data-augmented Phrase-level Alignment
Pritam Sarkar, Sayna Ebrahimi, Ali Etemad +3
Despite their significant advancements, Multimodal Large Language Models (MLLMs) often generate factually inaccurate information, referred to as hallucination. In this work, we add…