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20242026
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cs.CV2026

RIVER: A Real-Time Interaction Benchmark for Video LLMs

Yansong Shi, Qingsong Zhao, Tianxiang Jiang +3

The rapid advancement of multimodal large language models has demonstrated impressive capabilities, yet nearly all operate in an offline paradigm, hindering real-time interactivity…

cs.CV2026

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…

cs.CV2025

TimeLens: Rethinking Video Temporal Grounding with Multimodal LLMs

Jun Zhang, Teng Wang, Yuying Ge +4

This paper does not introduce a novel method but instead establishes a straightforward, incremental, yet essential baseline for video temporal grounding (VTG), a core capability in…

cs.CV2025

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…

cs.CV2025

Learning Goal-Oriented Vision-and-Language Navigation with Self-Improving Demonstrations at Scale

Songze Li, Zun Wang, Gengze Zhou +8

Goal-oriented vision-language navigation requires robust exploration capabilities for agents to navigate to specified goals in unknown environments without step-by-step instruction…

cs.CV2025

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…