MemSifter: Offloading LLM Memory Retrieval via Outcome-Driven Proxy Reasoning

2026-03-05T08:52:18Zbe7722530e26c02a93e9a4c3f1f16daa2a42d5d06297a0b6f0733f019461f8ef
LLM memoryRAGadversarial MLadvertising optimizationagent-user problemdata poisoningmedical AImodel evaluation/robustnessmodel supply chainmulti-agent systemsopen-source modelsprivacy leakagerecommender systemsshared-account abuse

What happened

Collection of recent arXiv papers (Mar 2026) focused on improvements to LLM long-term memory, retrieval-augmented generation (RAG), multi-round agentic reasoning, and industrial recommender/ranking systems. Key contributions include MemSifter (offloads memory retrieval to a small proxy model with RL training; code/weights released), AriadneMem and PlugMem (structured memory systems/graphs to enable efficient long-horizon agent memory), MA-RAG (multi-round agentic RAG for higher-fidelity medical reasoning; code released), and several industrial-scale ranking/recommendation advances (SORT, HAP,

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_ir
Record identifier
be7722530e26c02a93e9a4c3f1f16daa2a42d5d06297a0b6f0733f019461f8ef
Enrichment time
2026-03-05T08:52:18Z
AI-assisted enrichment
Yes

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