3 papers
cs.AI2026
Proposals and challenges for zero-knowledge verification of frontier AI training
Pierre Peigné, Ky Nguyen, Paul Wang
Proposals for Frontier AI rules often use cumulative training compute as the main criterion for identifying high-impact models. Recent governance analyses call zero-knowledge proof…
cs.LG2026
The Evaluation Game: Beyond Static LLM Benchmarking
Paul Wang, Jade Garcia-Bourrée, Anne-Marie Kermarrec +1
As jailbreaks, adversarially crafted inputs that bypass safety constraints, continue to be discovered in Large Language Models, practitioners increasingly rely on fine-tuning as a…
quant-ph2025
Compilation, Optimization, Error Mitigation, and Machine Learning in Quantum Algorithms
Shuangbao Paul Wang, Jianzhou Mao, Eric Sakk
This paper discusses the compilation, optimization, and error mitigation of quantum algorithms, essential steps to execute real-world quantum algorithms. Quantum algorithms running…