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Metis: Bridging Text and Code Memory for Self-Evolving Agents

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arXiv:2606. 24151v1 Announce Type: new Abstract: Self-evolving agents improve over time by distilling experience from past executions and reusing it in future tasks.

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Authors: Zijie Dai, Siuhin He, Hui Li, Qihui Zhou, Jiajun Li, Mingcong Song, Guoping Long, Hongjie Si, Xin Yao, Lin Zhang, James Cheng, Xiao Yan
Released: 2026-06-24 (15d ago)
Topic: Related to current project
Relation to my work: Read next because Metis: Bridging Text and Code Memory for Self-Evolving Agents overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: code, text, under, eval, compare, control, alone, language. Source: arxiv cs.CL (NLP).
arXiv: 2606.24151

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