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cs.CV2026
Scaling medical imaging report generation with multimodal reinforcement learning
Qianchu Liu, Sheng Zhang, Guanghui Qin +11
Frontier models have demonstrated remarkable capabilities in understanding and reasoning with natural-language text, but they still exhibit major competency gaps in multimodal unde…
cs.CV2026
RiskCueBench: Benchmarking Anticipatory Reasoning from Early Risk Cues in Video-Language Models
Sha Luo, Yogesh Prabhu, Timothy Ossowski +2
With the rapid growth of video centered social media, the ability to anticipate risky events from visual data is a promising direction for ensuring public safety and preventing rea…
cs.CV2024
OLIVE: Object Level In-Context Visual Embeddings
Timothy Ossowski, Junjie Hu
Recent generalist vision-language models (VLMs) have demonstrated impressive reasoning capabilities across diverse multimodal tasks. However, these models still struggle with fine-…