The surface code is a leading quantum error correction candidate for fault-tolerant quantum computing. Within this framework, Pauli-based computation eliminates Clifford gates at the cost of higher-weight multi-qubit operators that require large ancilla patches. The dominant bottleneck for scaling such systems across d...
Samuel A. Stein, Shu-Wen Kan, Charles Guinn et al.· Proceedings of the Internati...· 1 citation
The recent wave of one-step generative models, which compress the multi-step trajectory of diffusion via either distillation or learned flow maps, has reached an inflection point where they can generate high-quality images. Here, we ask a natural question that follows from these advances: what happens to the denoising...
Arnold Caleb Asiimwe, William Yang, Sanghyuk Chun et al.· 0 citations
Majority voting over sampled completions is the workhorse of test-time scaling, and reinforcement learning with verifiable rewards (RLVR) is the workhorse for making each completion better. The standard pipeline composes the two: train one policy with RLVR, then sample it many times and vote. We show that this composit...
Jonathan Williams, E. Tureci, Karthik R. Narasimhan· 0 citations
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