8 papers
PaperScope: A Multi-Modal Multi-Document Benchmark for Agentic Deep Research Across Massive Scientific Papers
Lei Xiong, Huaying Yuan, Zheng Liu +2
Leveraging Multi-modal Large Language Models (MLLMs) to accelerate frontier scientific research is promising, yet how to rigorously evaluate such systems remains unclear. Existing…
MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval
Huaying Yuan, Jian Ni, Zheng Liu +7
Accurately locating key moments within long videos is crucial for solving long video understanding (LVU) tasks. However, existing benchmarks are either severely limited in terms of…
VideoExplorer: Think With Videos For Agentic Long-Video Understanding
Huaying Yuan, Zheng Liu, Junjie Zhou +5
Long-video understanding~(LVU) is a challenging problem in computer vision. Existing methods either downsample frames for single-pass reasoning, sacrificing fine-grained details, o…
Task-Aware KV Compression For Cost-Effective Long Video Understanding
Minghao Qin, Yan Shu, Peitian Zhang +6
Long-video understanding (LVU) remains a severe challenge for existing multimodal large language models (MLLMs), primarily due to the prohibitive computational cost. Recent approac…
Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification
Minghao Qin, Xiangrui Liu, Zhengyang Liang +6
Multi-modal large language models (MLLMs) models have made significant progress in video understanding over the past few years. However, processing long video inputs remains a majo…
Memory-enhanced Retrieval Augmentation for Long Video Understanding
Huaying Yuan, Zheng Liu, Minghao Qin +5
Efficient long-video understanding~(LVU) remains a challenging task in computer vision. Current long-context vision-language models~(LVLMs) suffer from information loss due to comp…