LoCoMo

Headlines · 2

1. Oct 21
   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
2. Oct 20
   HKUST-led team's HeLa-Mem links distant memories for AI agents

   Researchers from HKUST (Guangzhou), Jilin University and the Chinese University of Hong Kong have proposed HeLa-Mem (Hebbian Learning Associative Memory), which targets the gap where an AI agent's relevant memories share little wording, and the paper was accepted to ACL 2026 Main with code published on GitHub. Each dialogue turn becomes an episodic memory node; links between nodes strengthen when they are retrieved together and decay when unused, while a reflection agent distils reusable semantic memory from densely connected nodes and flags isolated, stale nodes as forgetting candidates. Retrieval runs both a similarity/keyword/time path and an association-spreading path, merging results with semantic memory for the LLM; on LoCoMo with GPT-4o-mini, the authors report F1 of 40.14 (multi-hop), 47.29 (temporal), 29.70 (open-domain) and 51.89 (single-hop), using about 1010 retrieval-context tokens on average, versus roughly 2000 cited for MemoryOS and about 16910 for full-dialogue input. The authors note association weights must accumulate through interaction, leaving a cold-start challenge when history is thin, and that the distilled knowledge depends on the base LLM's capability.

   36氪 人工智能 · 🔥 0

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