From the 1 of 6 linked papers with an AI index.
6 papers
A Neurosymbolic Approach to Natural Language Formalization and Verification
Chenyang An, Sam Bayless, Stefano Buliani +27
The paper presents ARc, a system that combines large language models with automated reasoning to formally translate natural‑language policies and verify their logical correctness,…
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…
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…
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…
Scheherazade: Evaluating Chain-of-Thought Math Reasoning in LLMs with Chain-of-Problems
Stephen Miner, Yoshiki Takashima, Simeng Han +4
Benchmarks are critical for measuring Large Language Model (LLM) reasoning capabilities. Some benchmarks have even become the de facto indicator of such capabilities. However, as L…
Quantum Circuit Reconstruction from Power Side-Channel Attacks on Quantum Computer Controllers
Ferhat Erata, Chuanqi Xu, Ruzica Piskac +1
The interest in quantum computing has grown rapidly in recent years, and with it grows the importance of securing quantum circuits. A novel type of threat to quantum circuits that…