{
  "id": 19143,
  "url": "https://arxiv.org/abs/2608.12990",
  "title": "LycheeMemory V2: Efficient Long-Term Memory for LLM Agents via Semantic Segment-Level Consolidation",
  "summary": "Long-horizon LLM agents must preserve information from past interactions to support future tasks. Existing memory systems typically rely on eager consolidation, invoking LLMs after each interaction to extract, summarize, or update memories. This design makes memory construction increasingly costly as conversations grow. Coarse summarization can reduce construction cost but risks discarding fine-grained contextual evidence, whereas larger retrieval contexts or multi-hop LLM reasoning shift the ov",
  "authors": "Dongfang Li, Zixuan Liu, Junmai Wang, Jiahe Huang, Fuhao Li, Bonian Jia",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-12T20:00:00.000Z",
  "fetched_at": "2026-08-14T05:10:49.168Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/19143",
  "original_url": "https://arxiv.org/abs/2608.12990",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}