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https://arxiv.org/html/2608.02613v1
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
https://arxiv.org/list/cs.AI/new
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https://arxiv.org/html/2608.03048v1
com/JetAstra/PI-Mem
Introduction
The ability to reason over long contexts is increasingly important for large language models (LLMs), supporting applications such as long-document question answering (Gemini Team 2025; Yang et al
https://arxiv.org/html/2501.13956v1
com
Abstract
We introduce Zep, a novel memory layer service for AI agents that outperforms the current state-of-the-art system, MemGPT, in the Deep Memory Retrieval (DMR) benchmark
https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands
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https://arxiv.org/list/cs.CL/new
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends
https://arxiv.org/html/2607.22511v2
The source code, formal library, and run records are available at https://github
https://arxiv.org/pdf/2608.03883
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https://arxiv.org/pdf/2006.02318
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https://arxiv.org/pdf/2608.01366
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https://arxiv.org/src/2205.11916v1
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https://arxiv.org/pdf/2608.04341
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https://arxiv.org/pdf/2608.02764
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https://arxiv.org/pdf/2607.28577v1
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https://arxiv.org/src/2205.11916v3
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https://arxiv.org/pdf/2607.27188v1
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https://arxiv.org/pdf/2608.03063
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https://arxiv.org/pdf/2608.02122
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https://arxiv.org/src/2006.02759
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https://arxiv.org/pdf/2508.11152
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https://arxiv.org/pdf/2608.01785
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