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arXiv:2509.00009v2 Announce Type: replace-cross Abstract: Engineered injection and extraction systems that create chaotic advection are promising procedures for enhancing mixing between two species. Mixing efficiencies...
arXiv:2510.24855v3 Announce Type: replace-cross Abstract: A liquid drop impacting a non-wetting rigid substrate laterally spreads, then retracts, and finally jumps off again. An elastic solid,...
arXiv:2512.05477v2 Announce Type: replace-cross Abstract: Quantum geometry is a differential geometry based on quantum mechanics. It is related to various transport and optical properties in...
arXiv:2512.22826v2 Announce Type: replace-cross Abstract: The Parallel Minority Game (PMG) is a synchronous adaptive multi-agent model that exhibits active-absorbing transitions characteristic of non-equilibrium statistical systems....
arXiv:2601.06320v2 Announce Type: replace-cross Abstract: Inferring high-dimensional physical states from sparse, ad-hoc sensor arrays is a fundamental challenge across AI for Science, yet standard architectures...
arXiv:2601.13420v2 Announce Type: replace-cross Abstract: We demonstrate a neutral atom networking node that combines high photon collection efficiency with high atom photon entanglement fidelity in...
arXiv:2601.19584v2 Announce Type: replace-cross Abstract: The migration of low-mass planets is tightly controlled by the torques exerted by both gas and solids in their natal...
arXiv:2601.19900v1 Announce Type: new Abstract: Bit truncation has demonstrated great potential to enable run-time quality-power adaptive data storage, thereby optimizing the power/energy efficiency of approximate...
arXiv:2601.19901v1 Announce Type: new Abstract: Rendering for light field displays (LFDs) requires rendering of dozens or hundreds of views, which must then be combined into...
arXiv:2601.19902v1 Announce Type: new Abstract: Lengthening a computer memory's lifespan is important for e-waste and sustainability. Uneven wear of memory is a major barrier. The...
arXiv:2601.19903v1 Announce Type: new Abstract: Formal Verification (FV) relies on high-quality SystemVerilog Assertions (SVAs), but the manual writing process is slow and error-prone. Existing LLM-based...
arXiv:2601.19904v1 Announce Type: new Abstract: The exponential growth of large language models has outpaced the capabilities of traditional CPU and GPU architectures due to the...
arXiv:2601.19905v1 Announce Type: new Abstract: Silicon-based analog neural networks physically embody the ideal neural network model in an approximate way. We show that by retraining...
arXiv:2601.19906v1 Announce Type: new Abstract: Targeting error-tolerant applications, approximate circuits introduce controlled errors to significantly improve performance, power, and area (PPA) of circuits. In this...
arXiv:2601.19907v1 Announce Type: new Abstract: All-pairs shortest paths (APSP) remains a major bottleneck for large-scale graph analytics, as data movement with cubic complexity overwhelms the...
arXiv:2601.19908v1 Announce Type: new Abstract: The proliferation of large language models (LLMs) is accelerating the integration of multimodal assistants into edge devices, where inference is...
arXiv:2601.19909v1 Announce Type: new Abstract: Prime generation is a fundamental task in cryptography, number theory, and randomized algorithms. While the classical Sieve of Eratosthenes is...
arXiv:2601.19910v1 Announce Type: new Abstract: KV cache offloading enables long-context LLM inference by storing caches in CPU DRAM, but PCIe bandwidth limitations create severe bottlenecks....
arXiv:2601.19911v1 Announce Type: new Abstract: Modern OLAP systems have mitigated I/O bottlenecks via storage-compute separation and columnar layouts, but CPU costs in the execution layer...
arXiv:2601.19912v1 Announce Type: new Abstract: Large language models (LLMs) are highly compute- and memory-intensive, posing significant demands on high-performance GPUs. At the same time, advances...
arXiv:2601.19913v1 Announce Type: new Abstract: Distinguishing human-written Korean text from fluent LLM outputs remains difficult even for linguistically trained readers, who can over-trust surface well-formedness....
arXiv:2601.19914v1 Announce Type: new Abstract: Synthetic data has proven itself to be a valuable resource for tuning smaller, cost-effective language models to handle the complexities...
arXiv:2601.19915v1 Announce Type: new Abstract: We introduce the \emph{Arrow Language Model}, a neural architecture derived from an intuitionistic-logic interpretation of next-token prediction. Instead of representing...
arXiv:2601.19916v1 Announce Type: new Abstract: Large language models can generate fluent peer reviews, yet their assessments often lack sufficient critical rigor when substantive issues are...