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Nov 14Sat
  1. MarkTechPost59

    Stanford Research Open-Sources Memorilla, a Latent Memory Module for Frozen LLMs

    Stanford researchers have released Memorilla, an open-source 194M-parameter memory module that condenses a whole document collection into 16 memory tokens for a frozen LLM, with code, training recipes and checkpoints public under Apache 2.0. On FactKG, a frozen Qwen3-8B scored 84.33% with Memorilla versus 80.43% for full context, using 108x fewer document tokens, and it reported the highest average (49.68) across 8 benchmarks while losing on PubMedQA (59.00% vs 69.00% for LLMLingua-2). The quickstart requires one 80 GB CUDA GPU, and the full training recipe takes about 19 hours on 4 H100 GPUs.

Nov 6Fri
  1. Apple Machine Learning Research38

    Faster Retrieval for Better, More Efficient RAG

    Apple researchers present amortized maximum inner product search (MIPS), training small neural networks offline on a fixed key database to learn the support function of the key set, which is convex and whose gradient returns the best-matching key. SupportNet learns per-cluster support functions to route queries more accurately than centroid-based routing, while KeyNet rewrites queries before a standard IVF index; on Natural Questions, SupportNet reached 95% routing recall about 1.9× faster than centroid routing, and KeyNet cut the time to 99% recall by up to ~8×. The work was presented at ICML 2026.

Oct 28Wed
  1. MarkTechPost65

    Meet LEANN: An Open-Source Vector Index that Shrinks a 60M-Chunk RAG Index from 201 GB to 6 GB

    UC Berkeley's Sky Computing Lab built LEANN, an MIT-licensed vector index on FAISS that stores a pruned graph and recomputes embeddings at query time instead of saving them, shrinking a 60M-chunk Wikipedia index from 201 GB to 6 GB in the repo benchmark. The paper, which won Best Research Paper at MLSys 2026, reports matching HNSW downstream accuracy (25.5% on NQ) at 90% recall using 4 GB instead of 188 GB, at the cost of slower retrieval (2.48 s vs 0.05 s on NQ). It ships apps for documents, Apple Mail, Chrome history, WeChat, iMessage and chat exports, plus an MCP server for Claude Code.