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ARXIV:2606.03544 · AGENTS · SUBMITTED 03 JUN · 20:47 UTC · FRESHNESS FRESH
ARXIV:2606.03544AGENTSSUBMITTED 03 JUN · 20:47 UTCFRESHNESS FRESHLinyue Pan · Yaoming Zhu · Lin Qiu · Xuezhi Cao · Xunliang Cai · arXiv
SAGE evaluates socialized evolution in agent ecosystems, showing peer experience can unlock breakthroughs for plateaued agents, especially with abstracted knowledge.
Opportunity summary
Pain SAGE evaluates socialized evolution in agent ecosystems, showing peer experience can unlock breakthroughs for plateaued agents, especially with abstracted knowledge.
Evidence 0 refs | 3 sources | 50% coverage
Blocker Evidence unverified
SAGE evaluates socialized evolution in agent ecosystems, showing peer experience can unlock breakthroughs for plateaued agents, especially with abstracted knowledge. Yet agents increasingly operate alongside peers whose strategies and outcomes are publicly visible.
Self-improving language agents are typically evaluated in isolation: an agent attempts a task, receives feedback, and iteratively refines its own behavior. Yet agents increasingly operate alongside peers whose strategies and outcomes are publicly visible.
ScienceToStartup currently rates this 4.0/10 on the public viability pass. This raises an under-studied question: when does shared experience produce improvements that self-improvement alone cannot achieve?
Agents moved forward this cycle; last verified June 2026. Public score 4.0/10.
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SAGE evaluates socialized evolution in agent ecosystems, showing peer experience can unlock breakthroughs for plateaued agents, especially with abstracted knowledge.
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10.48550/arXiv.2606.03544SAGE evaluates socialized evolution in agent ecosystems, showing peer experience can unlock breakthroughs for plateaued agents, especially with abstracted knowledge.
Abstract
Self-improving language agents are typically evaluated in isolation: an agent attempts a task, receives feedback, and iteratively refines its own behavior. Yet agents increasingly operate alongside peers whose strategies and outcomes are publicly visible. This raises an under-studied question: when does shared experience produce improvements that self-improvement alone cannot achieve? We introduce SAGE (Social Agent Group Evolution),an evaluation framework that compares two compute-matched conditions: SocialEvo, where agents from five distinct model families co-evolve with access to all peers' histories; and SelfEvo, where each agent receives the same number of task attempts but sees only its own past, which is conventional in self-improving agent studies. We instantiate SAGE in three arenas: open-ended ML research, long-horizon economic planning, and strategic multiplayer play, evaluated across multiple evolutionary rounds. We find that group history is not a universal amplifier: the strongest agent does not exceed its self-evolution ceiling. However, agents that plateau under self-improvement can achieve significant breakthroughs when peer experience is available. In competitive settings, counterfactual controls reveal that agents improve generally rather than developing opponent-specific strategies. Across different forms of shared history, filtered peer traces and reflective summaries often outperform raw logs, indicating that social gains depend on abstraction rather than exposure volume. These findings reveal that peer-history gains are agent-specific, arena-dependent, and contingent on the capacity to abstract transferable knowledge from public traces.
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PROBLEM
SAGE evaluates socialized evolution in agent ecosystems, showing peer experience can unlock breakthroughs for plateaued agents, especially with abstracted knowledge. Yet agents increasingly operate alongside peers whose strategies and outcomes are publicly visible.
METHOD
Self-improving language agents are typically evaluated in isolation: an agent attempts a task, receives feedback, and iteratively refines its own behavior. Yet agents increasingly operate alongside peers whose strategies and outcomes are publicly visible.
RESULT
ScienceToStartup currently rates this 4.0/10 on the public viability pass. This raises an under-studied question: when does shared experience produce improvements that self-improvement alone cannot achieve?
WHY NOW
Agents moved forward this cycle; last verified June 2026. Public score 4.0/10.
{"file name": "input.pdf", "number of pages": 13, "author": "Linyue Pan; Yaoming Zhu; Lin Qiu; Xuezhi Cao; Xunliang Cai", "title": "SAGE: A Quantitative Evaluation of Socialized Evolution in Agent Ecosystems"
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SAGE evaluates socialized evolution in agent ecosystems, showing peer experience can unlock breakthroughs for plateaued agents, especially with abstracted knowledge.
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4.0/10 public viability
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