AI RESEARCH
OmniMem: Scalable and Adaptive Memory Retrieval for Long Video Generation
arXiv CS.CV
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ArXi:2605.30519v1 Announce Type: new Autoregressive (AR) video generation extends videos by producing latent chunks sequentially, but scaling to long videos requires repeated access to a growing historical KV cache. Existing methods reduce this cost by truncating the KV cache or compressing it into implicit memory, but both lose explicit access to query-relevant historical details. We propose OmniMem, an explicit full-range memory retrieval framework that performs sparse KV retrieval over the historical cache.