Reliable online video question answering requires tracking state transitions while selectively abstaining when visual evidence is insufficient. Existing benchmarks focus on static recognition or long-range retrieval, rarely evaluating these coupled capabilities under evolving and incomplete evidence. We present STORM-B...
Si-Ru Zhong, Sheng-Han Tan, Rihong Yan et al.· 0 citations
Hybrid architectures combining linear sequence models with softmax attention provide an effective balance between efficient long-context modeling and precise token retrieval. Existing designs such as Native Hybrid Attention (NHA) combine compressed long-term states with sliding-window attention, but their exact attenti...
Rui-Jie Li, Jia-Xi Hu, Shi-Yu Wang et al.· 0 citations
Prefix-Steered Recurrent Memory (PREM), a memory-token-free framework for frozen vision-language models (VLMs) that separates video ingestion from query answering, consistently outperforms frozen baselines at every evaluated visual budget.
Si-Ru Zhong, Qiong-Yan Wang, Xiao-Hui Lv et al.· 0 citations
The Continuous Evolution Pool (CEP), a replay-free framework that maintains a dynamic pool of specialized forecasters, is proposed, which employs a retrieval mechanism to identify the nearest concept based on gene similarity, an evolution strategy to spawn new forecasters upon detecting distribution shifts, and an elim...
Tianxiang Zhan, Ming Jin, Yuanpeng He et al.· arXiv.org· 3 citations
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