GUARDTs: Decentralized Access Control for Replicated Data Types
arXiv:2611.08083v1 Announce Type: cross Abstract: Replicated data types providing strong eventual consistency offer a principled foundation for developing decen…
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arXiv:2611.08083v1 Announce Type: cross Abstract: Replicated data types providing strong eventual consistency offer a principled foundation for developing decen…
arXiv:2611.07164v1 Announce Type: cross Abstract: Provenance Identity Continuity (PIC) represents an authority-use event as an operation/resource behavior situa…
arXiv:2611.07159v1 Announce Type: cross Abstract: Proof-of-Possession (PoP) establishes that an executor controls an artifact (key, token, credential, or capabi…
arXiv:2611.06989v1 Announce Type: cross Abstract: Enterprises run business transactions through multi-agent AI systems spanning clouds, large language models (L…
arXiv:2611.06984v1 Announce Type: cross Abstract: Reinforcement learning post-training improves the capabilities of large language models, but generating traini…
arXiv:2611.08108v1 Announce Type: new Abstract: Field devices deployed today will still be producing records when quantum computers may break their signatures, …
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…