Failure-Transparent Agents: Benchmarking Post-Failure Reporting in Tool-Using Language Models
cs.AI
Submitted: 2026-09-28
Updated: 2026-09-28
Comments: 5 pages, 1 figure, 2 tables. Submitted to the 2027 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2027)
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Tool Learning with Foundation Models
- WebSuite: Systematically Evaluating Why Web Agents Fail
- Failure Makes the Agent Stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions
- Are Your Agents Upward Deceivers?
- ReliabilityBench: Evaluating LLM Agent Reliability Under Production-Like Stress Conditions
- Evidence-Bound Autonomous Research (EviBound): A Governance Framework for Eliminating False Claims
- Agent-SafetyBench: Evaluating the Safety of LLM Agents
- AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions
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