Problem
Research questions and friction points this paper is trying to address.
privacy-constrained records
cross-record inference
evidence from free-text narratives
privacy transformations
reasoning over hybrid records
CIPHER: Benchmarking Cross-record Inference over Privacy-Hardened Evidence Records
🤖 AI Summary
CIPHER通过引入包含专家验证问题的基准，评估不同系统在隐私保护记录上的跨记录推理能力，旨在解决隐私约束下记录推理的问题。
📝 Abstract
Reasoning over privacy-constrained records requires combining structured attributes with evidence from free-text narratives. We introduce CIPHER (Cross-record Inference over Privacy-Hardened Evidence Records), a benchmark of expert-validated questions from consumer-finance, clinical, and law-enforcement records. The questions cover common tabular operations and include executable SQL supervision. We evaluate retrieval, prompting, table-specialist, and hybrid symbolic-neural systems under native redaction and surrogate-based evidence restoration. All system families exhibit substantial failures even when supporting records are provided. Most errors arise from incorrect record selection and predicate interpretation rather than arithmetic execution. Privacy transformations have non-uniform effects, sometimes obscuring necessary evidence and sometimes reducing distraction. CIPHER provides a reproducible testbed for diagnosing these failures and assessing how transformations of sensitive text affect reasoning over hybrid records.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Cross-record Inference
Privacy-Hardened Evidence Records
Hybrid Symbolic-Neural Systems
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