4 papers
R-AVST: Empowering Video-LLMs with Fine-Grained Spatio-Temporal Reasoning in Complex Audio-Visual Scenarios
Lu Zhu, Tiantian Geng, Yangye Chen +3
Recently, rapid advancements have been made in multimodal large language models (MLLMs), especially in video understanding tasks. However, current research focuses on simple video…
A Language-Signal-Vision Multimodal Framework for Multitask Cardiac Analysis
Yuting Zhang, Tiantian Geng, Luoying Hao +9
Contemporary cardiovascular management involves complex consideration and integration of multimodal cardiac datasets, where each modality provides distinct but complementary physio…
CVBench: Benchmarking Cross-Video Synergies for Complex Multimodal Reasoning
Nannan Zhu, Yonghao Dong, Teng Wang +9
While multimodal large language models (MLLMs) exhibit strong performance on single-video tasks (e.g., video question answering), their capability for spatiotemporal pattern reason…
LongVALE: Vision-Audio-Language-Event Benchmark Towards Time-Aware Omni-Modal Perception of Long Videos
Tiantian Geng, Jinrui Zhang, Qingni Wang +3
Despite impressive advancements in video understanding, most efforts remain limited to coarse-grained or visual-only video tasks. However, real-world videos encompass omni-modal in…