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Compaction beats full transcript in memory

Original title: Compaction, decay and reinforcement in a two-tier conversational memory: a paired evaluation against retrieval-augmented generation

arXiv cs.AI / cs.LG / cs.CLby Osamudiamen Edogun ()1 min read
AI summary · x-ai/grok-4.7Summaries by Vani AI

Compaction scores 71.4 percent vs 64.6 percent with 34 percent fewer tokens on LoCoMo.

Two-tier conversational memory compared using LoCoMo dataset. Compaction stores atomic facts while retrieval-augmented generation keeps transcripts. Compaction wins on comparable work but loses on adversarial sets where baseline leads by 14.6 points.

Key facts
  • 512 questions where methods disagree
  • Compaction at 71.4 percent vs 64.6 percent
  • 34 percent fewer prompt tokens
  • Lead falls to 2.0 points on adversarial set
  • Judge bias ruled out by token overlap analysis
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From the original article

1 min read at arxiv.org

A conversational agent that remembers has to decide what to keep. Retrieval-augmented generation keeps the transcript and searches it; the alternative is to compact each turn into atomic facts and search those.

arXiv cs.AI / cs.LG / cs.CL

By Osamudiamen Edogun · arxiv.org

Read the full article at arXiv cs.AI / cs.LG / cs.CL

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.