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arXiv:2603.00889v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently exhibited remarkable reasoning capabilities, largely enabled by supervised fine-tuning (SFT)- and reinforcement learning (RL)-based...
arXiv:2603.00890v1 Announce Type: new Abstract: Smart contracts underpin high-value ecosystems such as decentralized finance (DeFi), yet recurring vulnerabilities continue to cause losses worth billions of...
arXiv:2603.00892v1 Announce Type: new Abstract: This paper introduces a novel design for a robotic hand based on parallel mechanisms. The proposed hand uses a triple-symmetric...
arXiv:2603.00895v1 Announce Type: new Abstract: Grading in large undergraduate STEM courses often yields minimal feedback due to heavy instructional workloads. We present a large-scale empirical...
arXiv:2603.00897v1 Announce Type: new Abstract: Large language models are increasingly used to produce runnable software. In practice, security is often addressed through a Detect--Repair--Verify (DRV)...
arXiv:2603.00898v1 Announce Type: new Abstract: Randomized parallel algorithms for many fundamental problems achieve optimal linear work in expectation, but upgrading this guarantee to hold with...
arXiv:2603.00902v1 Announce Type: new Abstract: Modern generative agents such as OpenClaw - an open-source, self-hosted personal assistant with a community skill ecosystem, are gaining attention...
arXiv:2603.00903v1 Announce Type: new Abstract: Inspired by the human learning and memory system, particularly the interplay between the hippocampus and cerebral cortex, this study proposes...
arXiv:2603.00904v1 Announce Type: new Abstract: When neural networks (NNs) are used as a type of nonlinear parametric representation to solve partial differential equations (PDEs), they...
arXiv:2603.00905v1 Announce Type: new Abstract: Multi-modal Large Language Models (MLLMs) have demonstrated strong capabilities in general-purpose perception and reasoning, but they still struggle with tasks...
arXiv:2603.00906v1 Announce Type: new Abstract: Look-Up Table based methods have emerged as a promising direction for efficient image restoration tasks. Recent LUT-based methods focus on...
arXiv:2603.00907v1 Announce Type: new Abstract: The growing computational and memory demands of the Key-Value (KV) cache significantly limit the ability of Large Language Models (LLMs)....
arXiv:2603.00908v1 Announce Type: new Abstract: Underwater optical imaging is severely hindered by scattering, but polarization imaging offers the unique dual advantages of descattering and shape-from-polarization...
arXiv:2603.00909v1 Announce Type: new Abstract: Coarse-grained reconfigurable arrays (CGRAs) have attracted growing interest because they exhibit performance and energy efficiency competitive with ASICs while maintaining...
arXiv:2603.00910v1 Announce Type: new Abstract: Layer-wise capacity in large language models is highly non-uniform: some layers contribute disproportionately to loss reduction while others are near-redundant....
arXiv:2603.00911v1 Announce Type: new Abstract: The identification of repeating patterns in discrete grids is rudimentary within symbolic reasoning, algorithm synthesis and structural optimization across diverse...
arXiv:2603.00912v1 Announce Type: new Abstract: Current multi-view indoor 3D object detectors rely on sensor geometry that is costly to obtain (i.e., precisely calibrated multi-view camera...
arXiv:2603.00913v1 Announce Type: new Abstract: Compliance control is essential for safe physical interaction, yet its adoption is limited by hardware requirements such as force torque...
arXiv:2603.00917v1 Announce Type: new Abstract: Small open-source language models are gaining attention for low-resource healthcare settings, but their reliability under different prompt phrasings remains poorly...
arXiv:2603.00918v1 Announce Type: new Abstract: Text-to-image generation powers content creation across design, media, and data augmentation. Post-training of text-to-image generative models is a promising path...
arXiv:2603.00919v1 Announce Type: new Abstract: Large language models (LLMs) have shown great promise for autonomous driving. However, discretizing numbers into tokens limits precise numerical reasoning,...
arXiv:2603.00921v1 Announce Type: new Abstract: Data quality (DQ) and transparency of secondary data are critical factors that delay the adoption of clinical AI models and...
arXiv:2603.00923v1 Announce Type: new Abstract: Interlinear glossed text (IGT) creation remains a major bottleneck in linguistic documentation and fieldwork, particularly for low-resource morphologically rich languages....
arXiv:2603.00924v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used for medical entity extraction, yet their confidence scores are often miscalibrated, limiting safe...