arXiv AI By Patrick Cooper, Alvaro Velasquez

DeFAb: A Verifiable Benchmark for Defeasible Abduction in Foundation Models

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arXiv:2606. 18557v1 Announce Type: new Abstract: A rule-based logic solver resolves every instance in our benchmark in under 50 microseconds with 100% accuracy; the best frontier language model reaches 65% at best and drops to 23.

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arXiv AI
Aug 3

ModelEquivBench: Certifying Multi-Relational Evaluation of LLM-Generated Optimization Models

arXiv:2607. 29431v1 Announce Type: new Abstract: Large language models increasingly generate optimization models from natural language, but existing evaluation often reduces a generated model and its ground truth to a single equivalent/not-equivalent verdict or an execution-success rate--labels that are neither independently checkable nor faithful to the multiple distinct senses in which two formulations can agree.

By Penglin Zhu, Jungang Xu