3 citations · 7 across the 4 of their papers we have counts for
5 papers · 1 filter
VideoThinker: Building Agentic VideoLLMs with LLM-Guided Tool Reasoning
Chenglin Li, Qianglong Chen, Feng Han +6
Long-form video understanding remains a fundamental challenge for current Video Large Language Models. Most existing models rely on static reasoning over uniformly sampled frames,…
VideoPro: Adaptive Program Reasoning for Long Video Understanding
Chenglin Li, Feng Han, Yikun Wang +9
Large language models (LLMs) have shown promise in generating program workflows for visual tasks. However, previous approaches often rely on closed-source models, lack systematic r…
Iterative Zoom-In: Temporal Interval Exploration for Long Video Understanding
Chenglin Li, Qianglong Chen, fengtao +1
Multimodal Large Language Models (MLLMs) have shown strong performance in video understanding tasks. However, they continue to struggle with long-form videos because of an ineffici…
VideoCogQA: A Controllable Benchmark for Evaluating Cognitive Abilities in Video-Language Models
Chenglin Li, Qianglong Chen, Zhi Li +2
Recent advancements in Large Video-Language Models (LVLMs) have led to promising results in multimodal video understanding. However, it remains unclear whether these models possess…
ERNIE-mmLayout: Multi-grained MultiModal Transformer for Document Understanding
Wenjin Wang, Zhengjie Huang, Bin Luo +8
Recent efforts of multimodal Transformers have improved Visually Rich Document Understanding (VrDU) tasks via incorporating visual and textual information. However, existing approa…