Search: “interconnects”

arXiv:2605.13315v1 Announce Type: cross Abstract: Biological neural networks (BNNs) have been established as a powerful and adaptive substrate that offer the potential for incredibly energy and data e

arXiv:2605.12728v1 Announce Type: cross Abstract: The power distribution engineering workforce faces a projected shortage of up to 1.5 million engineers by 2030, creating urgent demand for more access

arXiv:2605.13213v1 Announce Type: new Abstract: Multi-modal multi-agent systems (MM-MAS) have gained increasing attention for their capacity to enable complex reasoning and coordination across diverse

arXiv:2603.19185v2 Announce Type: replace Abstract: Synthetic data is often perceived as a silver-bullet solution to data anonymization and privacy-preserving data publishing. Drawn from generative mo

arXiv:2605.08488v1 Announce Type: cross Abstract: We develop a unified Lyapunov-integral quadratic constraint (IQC) framework for establishing uniform stability of first-order accelerated optimization

arXiv:2511.21104v3 Announce Type: replace Abstract: Large language models can generate plausible code, but remain brittle for formal verification in proof assistants such as Lean. A central scalabilit

arXiv:2605.10036v1 Announce Type: cross Abstract: As 6G evolves, the radio access network must transcend traditional automation to embrace agentic AI capable of perception, reasoning, and evolution. A

arXiv:2602.07126v2 Announce Type: replace Abstract: Synthetic tabular data has gained attention for enabling privacy-preserving data sharing. While substantial progress has been made in single-table s

arXiv:2602.12606v2 Announce Type: replace Abstract: Relational deep learning (RDL) has emerged as a powerful paradigm for learning directly on relational databases by modeling entities and their relat

arXiv:2605.08911v1 Announce Type: new Abstract: Autonomous vehicles need to perceive not only physical elements in the driving scene, such as lane lines and traffic lights, but also logical elements l

arXiv:2605.07364v1 Announce Type: new Abstract: Flight delays impose cascading operational and financial burdens across the aviation network, costing the U.S. economy billions of dollars annually by d

arXiv:2605.06947v1 Announce Type: new Abstract: While autoregressive models have advanced 3D generation, creating physically stable brick structures remains a challenge due to the strict requirements

arXiv:2605.04376v1 Announce Type: new Abstract: The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite thes

arXiv:2605.04222v1 Announce Type: cross Abstract: Real-world control systems must achieve long-horizon objectives (liveness) while respecting continuous-time safety constraints, a combination that mot

arXiv:2605.01400v1 Announce Type: cross Abstract: Educational recommender systems (ERSs) are becoming increasingly important in enhancing educational outcomes and personalizing learning experiences by

arXiv:2605.02106v1 Announce Type: new Abstract: Contemporary artificial intelligence systems achieve strong performance through large-scale parameterization, retrieval augmentation, and training on ex

arXiv:2511.10580v3 Announce Type: replace Abstract: Origami-inspired mechanisms can transform flat sheets into functional three-dimensional dynamic structures that are lightweight, compact, and capabl

arXiv:2510.08804v3 Announce Type: replace Abstract: We present MOSAIC, a multi-agent Large Language Model (LLM) framework for solving challenging scientific coding tasks. Unlike general-purpose coding

arXiv:2605.00394v1 Announce Type: new Abstract: We present Mesh Field Theory (MeshFT) and its neural realization, MeshFT-Net: a structure-preserving framework for mesh-based continuum physics that cle

arXiv:2505.11329v5 Announce Type: replace-cross Abstract: Distributed inference of large language models (LLMs) using tensor parallelism can introduce communication overheads of 20% even over GPUs con

arXiv:2604.27085v1 Announce Type: cross Abstract: Fine-tuning Large Language Models (LLMs) on consumer-grade GPUs is highly cost-effective, yet constrained by limited GPU memory and slow PCIe intercon

arXiv:2604.27478v1 Announce Type: new Abstract: Terrestrial network limitations drive the integration of non-terrestrial networks (NTNs), notably mega-constellations comprising thousands of low Earth

arXiv:2508.09547v2 Announce Type: replace-cross Abstract: We introduce Goal-Conditioned Visual Navigation Instruction Generation (GoViG), a new task that aims to generate contextually coherent navigat

arXiv:2511.03691v2 Announce Type: replace Abstract: Conventional fluid-driven soft grippers typically depend on external sources, which limit portability and long-term autonomy. This work introduces a

arXiv:2510.14438v2 Announce Type: replace Abstract: The hallmark of Deep Research agents lies in compositional reasoning, the capacity to aggregate distributed, heterogeneous information into coherent

arXiv:2604.25482v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for narrative generation, but their use in complex, multi-layered role-playing game (RPG) world

arXiv:2604.25296v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional

arXiv:2602.10298v2 Announce Type: replace Abstract: This paper investigates whether LMs recruit shared computational mechanisms for general Theory of Mind (ToM) and language-specific pragmatic reasoni

arXiv:2602.12134v2 Announce Type: replace Abstract: Existing work on value alignment typically characterizes value relations statically, ignoring how alignment interventions, such as prompting, fine-t

arXiv:2604.21694v1 Announce Type: cross Abstract: Video copy detection requires robust similarity estimation under diverse visual distortions while operating at very large scale. Although deep neural

arXiv:2604.21894v1 Announce Type: new Abstract: Designing multi-agent robotic systems requires reasoning across tightly coupled decisions spanning heterogeneous domains, including robot design, fleet

arXiv:2604.19795v1 Announce Type: new Abstract: We introduce prism{} (extbf{P}robabilistic extbf{R}etrieval with extbf{I}nformation-extbf{S}tratified extbf{M}emory), an evolutionary memory substrate f

arXiv:2604.16839v1 Announce Type: new Abstract: Long-term memory is a critical challenge for Large Language Model agents, as fixed context windows cannot preserve coherence across extended interaction

arXiv:2604.13102v1 Announce Type: cross Abstract: Enterprise software organizations face an escalating challenge in maintaining the integrity, security, and freshness of codebases that span hundreds o

arXiv:2510.08055v2 Announce Type: replace Abstract: Large Language Model (LLM) inference in production must meet stringent service-level objectives for both time-to-first-token (TTFT) and time-between

arXiv:2601.14053v2 Announce Type: replace-cross Abstract: The field of artificial intelligence has undergone a revolution from foundational Transformer architectures to reasoning-capable systems appro

arXiv:2604.15143v1 Announce Type: cross Abstract: This work simulates the developmental process of cortical neurogenesis, initiating from a single stem cell and governed by gene regulatory rules deriv

arXiv:2604.12270v1 Announce Type: new Abstract: Stereo video inpainting, which aims to fill the occluded regions of warped videos with visually coherent content while maintaining temporal consistency,

arXiv:2505.19261v2 Announce Type: replace-cross Abstract: Current text-to-image diffusion generation typically employs complete-text conditioning. Due to the intricate syntax, diffusion transformers (

arXiv:2604.12721v1 Announce Type: new Abstract: Clinical case formulation organizes patient symptoms and psychosocial factors into causal models, often using the 5P framework. However, constructing su

arXiv:2410.21316v2 Announce Type: replace-cross Abstract: Transformers and large language models~(LLMs) have seen rapid adoption in all domains. Their sizes have exploded to hundreds of billions of pa

arXiv:2604.09868v1 Announce Type: cross Abstract: Industrial standards and normative documents exhibit intricate hierarchical structures, domain-specific lexicons, and extensive cross-referential depe

arXiv:2604.10152v1 Announce Type: new Abstract: The Mixture-of-Experts (MoE) architecture has emerged as a promising approach to mitigate the rising computational costs of large language models (LLMs)

arXiv:2604.09943v1 Announce Type: new Abstract: Reservoir computing (RC) is a computational framework known for its training efficiency, making it ideal for physical hardware implementations. However,

arXiv:2604.08341v1 Announce Type: new Abstract: Current Human-Robot Interaction (HRI) systems for skill teaching are fragmented, and existing approaches in the literature do not offer a cohesive frame

arXiv:2604.06793v1 Announce Type: cross Abstract: Software documentation is crucial for repository comprehension. While Large Language Models (LLMs) advance documentation generation from code snippets