MemoryAgentBench
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- Raw-RAG Leads Compared Memory Systems in Conversation Benchmark Study
An arXiv preprint introduces Raw-RAG, a baseline that uses dense retrieval and reranking over raw conversation history to supply evidence to a reader LLM. Across LoCoMo, LongMemEval, MEME, and MemoryAgentBench, the authors report that Raw-RAG ranked first among the compared memory systems in six of seven benchmark-model settings, outperforming the strongest compared agentic-memory system by 0.13 to 5.53 points. Their evidence analysis found that broader coverage of necessary information—including answer values and the relations and dependency paths needed to derive them—could offset lower evidence utilization.
Hugging Face · Papers · 🔥 0
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