arXiv CS
open access
BLADE: Auditing Information Use for Failure Attribution in LLM Multi-Agent Systems
Large language model multi-agent systems extend individual agents' capabilities through collaboration across specialized roles, tools, and workflows. Yet collaboration makes failures harder to diagnose: one agent may misinterpret a correct result while others carry the mistake forward. Failure attri
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- BLADE: Auditing Information Use for Failure Attribution in LLM Multi-Agent Systems#1344276
- Auditing Agent Actions through Query-Conditioned Attribution#1118749
- Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systems#282771
- Grounded Checklist Partial Credit for Agent Skill Trajectories#780804
- Grounded Checklist Partial Credit for Agent Skill Trajectories#779429
Record · ID 1319060
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive