AgentProofBench: Benchmarking Reusable Verifiers for Web Agents
AgentProofBench is a benchmark for reusable verifiers in web agents. It pairs tests of a frozen acceptance rule with execution from identical saved openings, spanning 97 tasks, 79 families, and four Web services. Experiments with DeepSeek Flash and Pro report that complete-panel and decision-replay tests retained most source programs, and that deployment-state panel correctness separated assignments with correct delivery from those with panel errors. Neutral continuation achieved the highest correct delivery under the tested generic feedback, serving as a baseline for measuring a gate's added value. Released instructions, states, programs, rules, and trajectories link test failures to execution outcomes.
Open original source huggingface.coOne primary source; other links are context, not independent corroboration.
- Primary sourceHugging Face Daily Papers
- Discovery linkHugging Face
- Linked in sourceView arXiv page
- Linked in sourceView PDF
The paper page is linked. Peer review and findings have not been independently checked by AINewsIQ.
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- Original non-discussion link+5
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AgentProofBench is a benchmark for reusable verifiers in web agents. It pairs tests of a frozen acceptance rule with execution from identical saved openings, spanning 97 tasks, 79 families, and four Web services. Experiments with DeepSeek Flash and Pro report that complete-panel and decision-replay tests retained most source programs, and that deployment-state panel correctness separated assignments with correct delivery from those with panel errors. Neutral continuation achieved the highest correct delivery under the tested generic feedback, serving as a baseline for measuring a gate's added value. Released instructions, states, programs, rules, and trajectories link test failures to execution outcomes.
A READER'S EVIDENCE CHECKHow to read this signalSix questions about claims, sources, risks, and open checks
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- 01Who is making each claim?
The claimant and whether each claim was measured or asserted are not recorded in this public brief.
- 02What was actually tested?
Not recorded per claim. Check the source for sample size, tasks, model and benchmark versions, and reproducibility.
- 03Where are the sources?
Original link: huggingface.co. Brief basis: fetched source page. Primary page date and quote locations are not established in this panel.
- 04What could mislead?
Results are reported for DeepSeek Flash and Pro on a specific benchmark of web tasks; source claims not independently checked.
- 05What is at risk if wrong?
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- 06What would change the view?
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Key findings from the stored brief
- The benchmark spans 97 tasks, 79 families, and four Web services, with saved openings for paired tests.
- Across 48 families, complete-panel and decision-replay tests retained 82/96 Flash and 79/96 Pro source programs.
- Of 33 assignments with error-free panels, 32 were delivered correctly; of 11 with panel errors, only 1 was.
- Neutral continuation achieved the highest correct delivery under the tested generic feedback, serving as a baseline.
Results are reported for DeepSeek Flash and Pro on a specific benchmark of web tasks; source claims not independently checked.
This is a source-based abstract, not independent validation of the source's claims.
Evidence & sources
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Related archive coverage
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The paper page is linked. Peer review and findings have not been independently checked by AINewsIQ.
Timeline & updates
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Why this may matter
Reusable verification of web agents must follow changing requirements while supporting later execution. AgentProofBench offers a way to measure whether acceptance rules and program gates hold up at both requirement and policy levels, with released artifacts for tracing failures.
Limits and open questions
Results are reported for DeepSeek Flash and Pro on a specific benchmark of web tasks; source claims not independently checked.
Organization-specific financial, security, and operational effects require the organization's own context and review.
Discussion
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