arXiv AI
Relic: From Multi-Agent Collaboration to Persistent Organizational Capability
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arXiv AI
Sep 2
Runtime-Independent Persistent Agents: Preserving Identity, Memory, and Code Across Models, Harnesses, and Servers
arXiv:2609. 00546v1 Announce Type: cross Abstract: Agent systems are commonly described by the model and harness that currently produce their behavior.
arXiv AI
Jun 19
Before the Pull Request: Mining Multi-Agent Coordination
arXiv:2606. 19616v1 Announce Type: cross Abstract: Autonomous coding agents now open millions of pull requests, yet large-scale studies find their PRs are produced faster but accepted less often - a coordination and trust gap that pull-request-level telemetry cannot explain.
arXiv AI
Aug 25
Repo2Skill-Evo: Repository Skills Go Stale in Silence
arXiv:2608.21964v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate over evolving software repositories, where success depends on repository-specific procedural kno...
arXiv AI
Jun 9
Collaborative Human-Agent Protocol (CHAP)
arXiv:2606. 09751v1 Announce Type: new Abstract: Foundation models are moving from response generation into operational roles.
arXiv AI
2d ago
Worse Together: How Performance Breaks Down in Multi-User Multi-Agent Teams
The paper investigates how coordination among AI agents serving different users degrades performance compared to a single coordinating agent. Across five advanced models and 77 scenarios in four shared-resource environments—API key budgets, clinic calendars, personal assistant bookings, and merge queues—the study finds that multi‑agent teams consistently underperform, sometimes collapsing entirely, and that even with communication channels coordination overhead remains significant. The authors identify specific failure modes such as stalling, action overriding, and claim fabrication, and propose environment‑specific mitigations like team leads and procedural instructions, while releasing the MAMUBench benchmark for future research.
arXiv AI
Jul 14
Temporary Authority, Permanent Effects: Commit-Time Authorization for LLM Agents
arXiv:2607. 10487v1 Announce Type: cross Abstract: LLM agents can commit durable effects from authority evidence that was valid earlier in execution: a DOM snapshot, approval epoch, version witness, branch token, or worker result.