KV Cache

Paper: WeaveTime: Stream from Earlier Frames into Emergent Memory in VideoLLMs PDF: CVPR 2026 Open Access Supplement: CVPR 2026 Supplementary Material Project: WeaveTime Code: zhangyl4/weavetime Core Idea WeaveTime can be summarized as: ReKV-style historical visual KV memory + temporal-order SFT + uncertainty-gated coarse-to-fine retrieval. It does not introduce a new compressed KV format or a bounded long-term memory. Instead, it improves two parts of a ReKV-style streaming system: temporal interpretation: teach the Video-LLM to distinguish event order rather than treat video as an unordered bag of visual evidence; memory access: answer from the current/recent context when possible and retrieve historical KV only when the model appears uncertain. The individual ingredients are familiar. The paper’s main contribution is their integration and evaluation under a causal streaming VideoQA protocol. ...

Paper: StreamingVLM: Real-Time Understanding for Infinite Video Streams Project: StreamingVLM Code: mit-han-lab/streaming-vlm Datasets: Inf-Stream-Train / Inf-Stream-Eval Core Idea StreamingVLM is designed for a different target from most streaming VideoQA papers: it keeps watching a video and producing synchronized commentary, instead of waiting for a future question and then retrieving historical evidence. Its main idea is to align a simple streaming inference cache with the context pattern used during supervised fine-tuning. At inference time, the model keeps only: ...

Paper: MuKV: Multi-Grained KV Cache Compression for Long Streaming Video Question-Answering Code: IMBALDY/MuKV Background Long streaming VideoQA has a simple but painful constraint: the video keeps arriving, while the future user questions are unknown. KV-cache methods such as ReKV make this setting more practical. Instead of recomputing historical video tokens when a question arrives, the model can prefill the video stream in advance, store the visual KV cache, retrieve the relevant cache blocks later, and answer with much lower online cost. ...