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BLADE: Auditing Information Use for Failure Attribution in LLM Multi-Agent Systems

Paper recorded by Signals 4 on 2026-10-13 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-13 on arXiv · recorded by Signals 4 on 2026-10-14

Category: cs.CL · 自然语言处理 · first seen 2026-10-14

Abstract

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 attribution therefore seeks to identify the responsible agent and decisive error step. Recent methods tra

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#258 most recent of 660 cs.CL papers we have recorded · ↑ newer: OmniCompass: A Holistic Benchmark for Omni-Modal Video Grounding and U · ↓ older: Rubrics from the Task, Verdicts from Evidence: Pointwise Rubric Reward
Cite this page: BLADE: Auditing Information Use for Failure Attribution in LLM Multi-Agent Systems: the #258 most recent of 660 cs.CL papers we have recorded (as of 2026-10-13). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/blade-auditing-information-use-for-failure-attribution-in-llm-multi-agent-system.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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