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Failure-Transparent Agents: Benchmarking Post-Failure Reporting in Tool-Using Language Models

Paper recorded by Signals 4 on 2026-09-28 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-28 on arXiv · recorded by Signals 4 on 2026-09-29

Category: cs.AI · 人工智能 · first seen 2026-09-29

Abstract

Tool-using agents can fail twice: a required tool can fail, and the agent can then report success without the evidence needed to justify it. Existing benchmarks often entangle this reporting failure with tool selection, recovery, and environment dynamics. We introduce Failure-Transparent Agents (FTA), a controlled benchmark that fixes the failed observation and required evidence state before gener

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#10 most recent of 440 cs.AI papers we have recorded · ↑ newer: Shockingly Simple Self-retrospection Improves Agentic Models Without R · ↓ older: X-Reset: Scaling Object-Centric Reinforcement Learning via Cross-Embod
Cite this page: Failure-Transparent Agents: Benchmarking Post-Failure Reporting in Tool-Using Language Models: the #10 most recent of 440 cs.AI papers we have recorded (as of 2026-09-28). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/failure-transparent-agents-benchmarking-post-failure-reporting-in-tool-using-lan.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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