3 papers
cs.CV2026
BAP-MOS: Bandit-Based Adaptive Prompting for Boundary-Sensitive Multi-Organ Segmentation
Satvik Praveen, Shengji Jin, Ahmed Lamidi +2
Multi-organ ultrasound segmentation remains challenging when anatomically adjacent structures must be delineated jointly, as localized boundary errors can persist even when Dice sc…
cs.CV2026
How Should Video LLMs Output Time? An Analysis of Efficient Temporal Grounding Paradigms
Shengji Jin, Yuanhao Zou, Victor Zhu +2
While Multimodal Large Language Models (MLLMs) have advanced Video Temporal Grounding (VTG), existing methods often couple output paradigms with different backbones, datasets, and…
cs.CV2026
A.I.R.: Enabling Adaptive, Iterative, and Reasoning-based Frame Selection For Video Question Answering
Yuanhao Zou, Shengji Jin, Andong Deng +3
Effectively applying Vision-Language Models (VLMs) to Video Question Answering (VideoQA) hinges on selecting a concise yet comprehensive set of frames, as processing entire videos…