6 papers
STORM-Bench: Evaluating Online Video QA under Evolving and Incomplete Evidence
Siru Zhong, Shenghan Tan, Rihong Yan +6
Reliable online video question answering requires tracking state transitions while selectively abstaining when visual evidence is insufficient. Existing benchmarks focus on static…
PREM: Prefix-Steered Recurrent Memory for Long-Video Understanding
Siru Zhong, Qiongyan Wang, Xiaohui Lv +5
Long-video understanding must capture transient visual evidence under strict token budgets, yet existing methods compress frames, append memory tokens, or alter internal key-value…
ChineseVideoBench: Benchmarking Multi-modal Large Models for Chinese Video Question Answering
Yuxiang Nie, Han Wang, Yongjie Ye +15
This paper introduces ChineseVideoBench, a pioneering benchmark specifically designed for evaluating Multimodal Large Language Models (MLLMs) in Chinese Video Question Answering. T…
ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models
Yuanfeng Xu, Zehui Dai, Jian Liang +4
Small Language Models (SLMs) are a cost-effective alternative to Large Language Models (LLMs), but often struggle with complex reasoning due to their limited capacity and a tendenc…
SUMMA: A Multimodal Large Language Model for Advertisement Summarization
Weitao Jia, Shuo Yin, Zhoufutu Wen +6
Understanding multimodal video ads is crucial for improving query-ad matching and relevance ranking on short video platforms, enhancing advertising effectiveness and user experienc…
MEML-GRPO: Heterogeneous Multi-Expert Mutual Learning for RLVR Advancement
Weitao Jia, Jinghui Lu, Haiyang Yu +17
Recent advances demonstrate that reinforcement learning with verifiable rewards (RLVR) significantly enhances the reasoning capabilities of large language models (LLMs). However, s…