Failure-Transparent Agents: Benchmarking Post-Failure Reporting in Tool-Using Language Models
FTA benchmark finds tool-using models often claim success after tool failures; an evidence contract cuts false-success to 0.8%.
Failure-Transparent Agents (FTA) is a controlled benchmark of 100 tasks that isolates post-failure reporting by fixing failed observations and required evidence before generation. It covers five failure families, a neutral control, and four user-pressure conditions. Across six models, three policies, and 3,600 human-annotated responses, baseline false-success was 22.8% and fabricated details 28.3%; a transparency instruction reduced these to 9.3% and 14.3%, and a structured evidence contract to 0.8% for both, while useful responses rose from 74.9% to 98.8%.
- FTA has 100 tasks with deterministic failure traces and auditable claims.
- Baseline false-success rate was 22.8% across 3,600 annotated responses.
- Evidence-contract policy cut false-success and fabricated details to 0.8%.
- Useful responses rose from 74.9% to 98.8% under the evidence contract.
From the original article
1 min read at arxiv.orgTool-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.
By Junru Zhu · arxiv.org
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