ContractEval: Query-Conditioned Execution Matching for Procedural Instruction ConformanceContractEval: Query-Conditioned Execution Matching for Procedural Instruction Conformance
Computer Science > Artificial Intelligence [Submitted on 8 Sep 2026] Title:ContractEval: Query-Conditioned ExecutiComputer Science > Artificial Intelligence [Submitted on 8 Sep 2026] Title:ContractEval: Query-Conditioned Executi
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- Computer Science > Artificial IntelligenceComputer Science > Artificial Intelligence
- [Submitted on 8 Sep 2026][Submitted on 8 Sep 2026]
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Computer Science > Artificial Intelligence
[Submitted on 8 Sep 2026]
Title:ContractEval: Query-Conditioned Execution Matching for Procedural Instruction Conformance
View PDF HTML (experimental)Abstract:As LLM agents move from answering questions to carrying out procedures, failures can be unwarranted rather than visibly wrong: the final response looks acceptable even though the system skipped the check, branch, dependency, or invariant that made the answer justified. Output-only evaluation sees the answer, and trace-aware judging sees activity, but neither identifies which obligations were active for the query. We introduce CONTRACTEVAL, a diagnostic framework for making those active obligations explicit. It represents procedural instructions as query-active obligations and matches them against response or trace evidence, turning omissions, wrong branches, ordering errors, extra actions, invariant breaches, and output-contract violations into distinct conformance failures. On a controlled suite of audited procedural contracts, output-only and trace-aware LLM judges miss many injected structural failures; under gold expected and observed graphs, ContractEval detects and localizes all of them. LLM-backed extraction preserves much of this signal but remains calibration-sensitive. ContractEval is therefore not a compliance guarantee; it makes procedural conformance auditable rather than implicit in final-answer quality.
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Computer Science > Artificial Intelligence
[Submitted on 8 Sep 2026]
Title:ContractEval: Query-Conditioned Execution Matching for Procedural Instruction Conformance
View PDF HTML (experimental)Abstract:As LLM agents move from answering questions to carrying out procedures, failures can be unwarranted rather than visibly wrong: the final response looks acceptable even though the system skipped the check, branch, dependency, or invariant that made the answer justified. Output-only evaluation sees the answer, and trace-aware judging sees activity, but neither identifies which obligations were active for the query. We introduce CONTRACTEVAL, a diagnostic framework for making those active obligations explicit. It represents procedural instructions as query-active obligations and matches them against response or trace evidence, turning omissions, wrong branches, ordering errors, extra actions, invariant breaches, and output-contract violations into distinct conformance failures. On a controlled suite of audited procedural contracts, output-only and trace-aware LLM judges miss many injected structural failures; under gold expected and observed graphs, ContractEval detects and localizes all of them. LLM-backed extraction preserves much of this signal but remains calibration-sensitive. ContractEval is therefore not a compliance guarantee; it makes procedural conformance auditable rather than implicit in final-answer quality.
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Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
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scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
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arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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