Quantum Advantage in Local Certification of Graph Properties
arXiv:2611.08076v1 Announce Type: new Abstract: Local certification allows network vertices to verify global properties using certificates from an untrusted pro…
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arXiv:2611.08076v1 Announce Type: new Abstract: Local certification allows network vertices to verify global properties using certificates from an untrusted pro…
arXiv:2611.08060v1 Announce Type: new Abstract: The Common Community Physics Package (CCPP) is a framework designed to simplify the exchange of physics packages…
arXiv:2611.08023v1 Announce Type: new Abstract: Complete-block offloading reduces model residency but requires each transferred block to fit the GPU budget. We …
arXiv:2611.07996v1 Announce Type: new Abstract: Multi-agent reinforcement learning (MARL) is increasingly used in systems where many entities interact in a shar…
arXiv:2611.07928v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is a standard approach to enhance the reliability of large language model (…
arXiv:2611.07919v1 Announce Type: new Abstract: We present a novel approach for model checking fault-tolerant distributed algorithms: instead of building large,…
arXiv:2611.07535v1 Announce Type: new Abstract: Low latency is critical to user experience. As NVIDIA Blackwell and Rubin GPUs advance multi-die scaling, data p…
arXiv:2611.07496v1 Announce Type: new Abstract: Attention is a core building block of frontier models and often dominates compute-bound prefill at long context.…
arXiv:2611.07477v1 Announce Type: new Abstract: Tensor and sequence parallelism (TP+SP) and expert parallelism (EP) put collectives on the critical path of tran…
arXiv:2611.07211v1 Announce Type: new Abstract: Looped transformers scale inference-time reasoning by repeatedly reusing a shared core, increasing computation w…
arXiv:2611.07198v1 Announce Type: new Abstract: Each new GPU generation is showcased by its peak instruction rates, yet users hardly ever run instructions direc…
arXiv:2611.07149v1 Announce Type: new Abstract: Attention-FFN disaggregation (AFD) separates attention from the experts of a mixture-of-experts (MoE) model and …
arXiv:2611.07105v1 Announce Type: new Abstract: For sufficiently large transformer-based Large Language Models (LLMs), whose parameters cannot be retained in on…
arXiv:2611.07084v1 Announce Type: new Abstract: Matrix optimizers such as Muon update whole weight matrices, which conflicts with the element- or row-wise shard…
arXiv:2606.07334v5 Announce Type: replace Abstract: This report treats chord-symbol sequences as an interpretable, controllable time series for genre-local harm…
arXiv:2605.04998v4 Announce Type: replace Abstract: This paper treats chord progression generation as a standalone task and asks how much old-domain data must b…
arXiv:2603.04122v2 Announce Type: replace Abstract: Audio Super-Resolution is a set of techniques aimed at high-quality estimation of the given signal as if it …
arXiv:2611.08130v1 Announce Type: cross Abstract: Music source separation extracts vocals and instruments from a mixed recording, enabling remixing, content pro…
arXiv:2611.08092v1 Announce Type: cross Abstract: Real-time voice agents need a speech recognizer that never waits for future audio and whose memory per call do…
arXiv:2611.08251v1 Announce Type: new Abstract: Recent advances in speech generation have spurred the development of speech editing techniques. However, achievi…