From the 1 of 7 linked papers with an AI index.
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cs.LG2026
Learning Randomized Reductions
Ferhat Erata, Orr Paradise, Thanos Typaldos +4
Randomized self-reductions (RSRs) express using evaluated at random correlated points, enabling self-correcting programs, instance-hiding protocols, and applications in…
cs.LG2026
Fidelity Probes for Specification--Code Alignment
Ferhat Erata, Hao Zhou, Luke Huan
We introduce fidelity probes: natural-language questions generated from a reference artifact with code-derived ground-truth answers, answered from a candidate specification. The fr…
cs.LG2026
Learning How to Cube
Ferhat Erata, Sam Kouteili, Thanos Typaldos +4
Despite the effectiveness of Cube-and-Conquer (C&C) for solving challenging Boolean Satisfiability (SAT) problems, no prior work has shown that transformer-based models can learn e…