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A new open-source memory layer called Memvid claims to outperform all existing RAG systems, achieving +35% SOTA on LoCoMo and +76% on multi-hop reasoning, packaged as a single .mv2 file.
This paper introduces the Context Gathering Decision Process (CGDP), a POMDP framework to model LLM agent search behavior, proposing interventions that improve multi-hop reasoning and reduce token usage without performance degradation.
This paper introduces TGS-RAG, a bidirectional verification and completion framework that synergizes text-based and graph-based Retrieval-Augmented Generation to improve multi-hop reasoning accuracy.
ConlangCrafter is a multi-hop LLM pipeline that automates constructed language (conlang) creation by decomposing the process into modular stages including phonology, morphology, syntax, lexicon generation, and translation. The system leverages LLMs' metalinguistic reasoning with randomness injection and self-refinement to produce coherent and typologically diverse constructed languages.