9 papers
LongVPO: From Anchored Cues to Self-Reasoning for Long-Form Video Preference Optimization
Zhenpeng Huang, Jiaqi Li, Zihan Jia +6
We present LongVPO, a novel two-stage Direct Preference Optimization framework that enables short-context vision-language models to robustly understand ultra-long videos without an…
StreamForest: Efficient Online Video Understanding with Persistent Event Memory
Xiangyu Zeng, Kefan Qiu, Qingyu Zhang +9
Multimodal Large Language Models (MLLMs) have recently achieved remarkable progress in video understanding. However, their effectiveness in real-time streaming scenarios remains li…
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Desen Meng, Rui Huang, Zhilin Dai +8
While recent advances in reinforcement learning have significantly enhanced reasoning capabilities in large language models (LLMs), these techniques remain underexplored in multi-m…
VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning
Xinhao Li, Ziang Yan, Desen Meng +7
Reinforcement Learning (RL) benefits Large Language Models (LLMs) for complex reasoning. Inspired by this, we explore integrating spatio-temporal specific rewards into Multimodal L…
InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling
Yi Wang, Xinhao Li, Ziang Yan +13
This paper aims to improve the performance of video multimodal large language models (MLLM) via long and rich context (LRC) modeling. As a result, we develop a new version of Inter…
Online Video Understanding: OVBench and VideoChat-Online
Zhenpeng Huang, Xinhao Li, Jiaqi Li +7
Multimodal Large Language Models (MLLMs) have significantly progressed in offline video understanding. However, applying these models to real-world scenarios, such as autonomous dr…