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arXiv:2602.20083v2 Announce Type: replace Abstract: Deploying Retrieval-Augmented Generation (RAG) on edge devices is in high demand, but is hindered by the latency of massive data...
arXiv:2602.20156v3 Announce Type: replace Abstract: LLM agents are evolving rapidly, powered by code execution, tools, and the recently introduced agent skills feature. Skills allow users...
arXiv:2602.20205v2 Announce Type: replace Abstract: Multi-modal large language models (MLLMs) achieve strong visual-language reasoning but suffer from high inference cost due to redundant visual tokens....
arXiv:2602.20223v2 Announce Type: replace Abstract: Recently, TabPFN has gained attention as a foundation model for tabular data. However, it struggles to integrate heterogeneous modalities such...
arXiv:2602.20292v2 Announce Type: replace Abstract: Agentic AI systems are deployed with expectations of substantial productivity gains, yet rigorous empirical evidence reveals systematic discrepancies between pre-deployment...
arXiv:2602.20309v2 Announce Type: replace Abstract: Vision-language-action (VLA) models unify perception, language, and control for embodied agents but face significant challenges in practical deployment due to...
arXiv:2602.20541v2 Announce Type: replace Abstract: We study the problem of fairly allocating indivisible goods when limited sharing is allowed, that is, each good may be...
arXiv:2602.20561v2 Announce Type: replace Abstract: Task-based runtime systems provide flexible load balancing and portability for parallel scientific applications, but their strong scaling is highly sensitive...
arXiv:2602.20610v2 Announce Type: replace Abstract: Specifications are vital for ensuring program correctness, yet writing them manually remains challenging and time-intensive. Recent large language model (LLM)-based...
arXiv:2602.20630v2 Announce Type: replace Abstract: Keypoint-based matching is a fundamental component of modern 3D vision systems, such as Structure-from-Motion (SfM) and SLAM. Most existing learning-based...
arXiv:2602.20659v2 Announce Type: replace Abstract: Vision-language-action models must enable agents to execute long-horizon tasks under partial observability. However, most existing approaches remain observation-driven, relying on...
arXiv:2602.20685v2 Announce Type: replace Abstract: World foundation models aim to simulate the evolution of the real world with physically plausible behavior. Unlike prior methods that...
arXiv:2602.20697v2 Announce Type: replace Abstract: We propose an algorithm for the computational homogenization of locally periodic hyperelastic structures undergoing large deformations due to external quasi-static...
arXiv:2602.20714v2 Announce Type: replace Abstract: Reliable prediction of hydraulic performance is challenging for Piano Key Weir (PKW) design because discharge capacity depends on three-dimensional geometry...
arXiv:2602.20800v2 Announce Type: replace Abstract: In Generative Information Retrieval (GenIR), the bottleneck has shifted from generation to the selection of candidates, particularly for normative criteria...
arXiv:2602.20829v2 Announce Type: replace Abstract: Boolean Satisfiability (SAT) solving underpins a wide range of applications in Electronic Design Automation (EDA), particularly formal verification. However, this...
arXiv:2602.20871v2 Announce Type: replace Abstract: Bridging the sim-to-real gap is important for applying low-cost simulation data to real-world robotic systems. However, previous methods are severely...
arXiv:2602.20880v2 Announce Type: replace Abstract: Text-to-Image (T2I) diffusion models have demonstrated significant advancements in generating high-quality images, while raising potential safety concerns regarding harmful content...
arXiv:2602.20887v2 Announce Type: replace Abstract: The forest-of-refinement-trees approach allows for dynamic adaptive mesh refinement (AMR) at negligible cost. While originally developed for quadrilateral and hexahedral...
arXiv:2602.20903v2 Announce Type: replace Abstract: Visual Text Rendering (VTR) remains a critical challenge in text-to-image generation, where even advanced models frequently produce text with structural...
arXiv:2602.20945v2 Announce Type: replace Abstract: Large Language Models (LLMs) consistently benefit from scaled Chain-of-Thought (CoT) reasoning, but also suffer from heavy computational overhead. To address...
arXiv:2602.20971v2 Announce Type: replace Abstract: Bubeck and Sellke (2021) pose as an open problem the connection between the law of robustness and robust generalization. The...
arXiv:2602.20981v2 Announce Type: replace Abstract: Scaling multimodal alignment between video and audio is challenging, particularly due to limited data and the mismatch between text descriptions...
arXiv:2602.21022v2 Announce Type: replace Abstract: Common definitions of the "standard" LOCAL model tend to be sloppy and even self-contradictory on one point: do the nodes...