KV Cache

Series guide. This article is the bounded-memory thematic survey. Start with the development-history hub for the six-path map, read the ReKV note for the exact-archive baseline, and use the pipeline survey for the stage-by-stage architecture. A streaming Video-LMM has to make decisions before it knows which detail a future user will care about. ReKV avoids write-time eviction or compression by storing every generated visual KV block, then retrieves a small subset after the question is known. This does not recover unsampled pixels or information absent from those model states. Fixed-state methods make the opposite trade: they evict, merge, or summarize history during the stream so that memory no longer grows with video duration. ...

Paper: WeaveTime: Streaming from Earlier Frames into Emergent Memory in VideoLLMs Preprint (earlier title: Stream from Earlier Frames): arXiv:2602.22142 PDF: CVPR 2026 Open Access Supplement: CVPR 2026 Supplementary Material Project: WeaveTime Code: zhangyl4/weavetime Series guide. PCDF bounds when and how much history is read, not how much ReKV-style history is stored. See the bounded-memory survey for the resource comparison and the development-history hub for the complete series. Core Idea WeaveTime can be summarized as: ReKV-style historical visual KV memory + temporal-order SFT + uncertainty-gated coarse-to-fine retrieval. ...

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 Proceedings: CVPR 2026 Open Access Code: IMBALDY/MuKV Series guide. A fixed per-question read can still sit on a growing multi-grained archive. See the bounded-memory survey for that accounting and the development-history hub for the complete series. 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. ...