Search: “automated”

arXiv:2608.00004v1 Announce Type: new Abstract: Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whe

arXiv:2607.29422v1 Announce Type: cross Abstract: Automated vulnerability repair aims to reduce the time and effort required to patch security flaws from a vulnerability triage report. Recent agentic

arXiv:2607.28634v1 Announce Type: new Abstract: The estimation of item difficulty plays a key role in both formative assessment and large-scale high-stakes summative assessments. This study explores h

arXiv:2604.05150v2 Announce Type: replace-cross Abstract: We study compiled AI, a paradigm in which large language models generate executable code artifacts during a compilation phase, after which wor

arXiv:2607.29601v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) commonly adapts large language models using a single shared Low-Rank Adapter (LoRA). This shared optimization spa

arXiv:2607.26625v1 Announce Type: new Abstract: Accurate model evaluation in machine learning depends critically on how datasets are split into training and testing subsets. Standard random splitting

arXiv:2607.25494v1 Announce Type: cross Abstract: Finite-precision arithmetic unavoidably introduces numerical approximation errors. Numerical computations may use insufficient precision or an imprope

arXiv:2607.22917v1 Announce Type: new Abstract: Large Language Model (LLM) agents have significantly improved coding and programming workflows. Claude Code, in particular, is one of the most powerful

arXiv:2607.22954v1 Announce Type: new Abstract: Objective: To characterize the kinds of internal documentation inconsistencies a general-domain large language model (LLM) can surface from real-world d

arXiv:2601.10554v3 Announce Type: replace Abstract: The efficacy of autonomous driving systems hinges critically on robust prediction and planning capabilities. However, current benchmarks are impeded

arXiv:2607.19912v1 Announce Type: cross Abstract: In efforts to increase research efficiency and availability, a digital twin of our research tractor (AMX G-trac) is created, focusing especially on th

arXiv:2607.19374v1 Announce Type: new Abstract: Recent formal reasoning systems have reached IMO-level performance, yet they leave a fragmented landscape: algebra and number theory are handled in Lean

arXiv:2607.12122v1 Announce Type: new Abstract: We present an agentic approach to autonomous neural operator discovery based on an AI scientific community, which consists of a swarm of virtual laborat

arXiv:2607.10183v2 Announce Type: replace-cross Abstract: Running large language models on consumer devices such as laptops and desktops is challenging because model weights often exceed GPU memory ca

arXiv:2607.07498v1 Announce Type: cross Abstract: Testing is a major effort for the gaming industry, requiring a significant part of development budget and people power. We present a case study on a d

arXiv:2607.05409v1 Announce Type: cross Abstract: Introductory programming instruction relies on hands-on practice and short learning activities to support mastery of foundational concepts. Although m

arXiv:2607.06150v1 Announce Type: new Abstract: Reliable seam segmentation is essential for autonomous robotic welding in construction, where harsh illumination, specular reflections, and thin weld ge

arXiv:2607.05915v1 Announce Type: new Abstract: PCB routing is the task of connecting the nets of a board with copper traces under strict design rules, yet learning-based methods still lag behind rule

arXiv:2604.02537v2 Announce Type: replace Abstract: All-atom molecular dynamics (MD) simulations can predict polymer properties from molecular structure, yet their execution requires specialized exper

arXiv:2607.06248v1 Announce Type: new Abstract: Validation of robotic systems critically depends on the operating conditions under which they are assessed. Scenario selection and variation are often m

arXiv:2406.07089v4 Announce Type: replace Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have shown promise for remote sensing tasks such as visual question answering and scene

arXiv:2607.02564v1 Announce Type: cross Abstract: Computational models of the human heart are widely used to study electromechanical and fluid-dynamical cardiac function and to support applications su

arXiv:2607.03166v1 Announce Type: cross Abstract: Template-based contrastive synthesis is scalable, but its candidates often differ only in a few entity-slots while sequence-level optimization spreads

arXiv:2607.02432v1 Announce Type: new Abstract: Scalable and reliable grading of command-line examinations remains a challenge in computing education, where rising enrolments make manual marking diffi

arXiv:2607.02230v1 Announce Type: cross Abstract: The complexity of waste disposal regulations across European countries poses significant challenges for the residents and hinders the transition to a

arXiv:2607.01457v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly applied to resume optimization for applicant tracking systems, introducing hallucination failures distin

arXiv:2507.22063v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) for code generation (i.e., Code LLMs) have demonstrated impressive capabilities in AI-assisted software developme

arXiv:2601.15212v2 Announce Type: replace Abstract: Training deep computer vision models requires manual oversight or hyperparameter tuning of the learning rate (LR) schedule. While existing adaptive

arXiv:2606.31332v1 Announce Type: new Abstract: Protein automodeling from cryo-EM density maps faces unique challenges in enforcing physicochemical validity and managing conformational heterogeneity.

arXiv:2602.18767v3 Announce Type: replace-cross Abstract: In Machine-Assisted Theorem Proving, a theorem proving agent searches for a sequence of expressions and tactics that can prove a statement in

arXiv:2606.31976v1 Announce Type: new Abstract: Human-labeled data are widely used as reference annotations in ML, despite known variability across annotators in many expert-driven domains. In additio

arXiv:2606.30801v1 Announce Type: new Abstract: Personalization algorithms determine what content users encounter on online platforms. Auditing these systems is difficult because independent auditors

arXiv:2606.30309v1 Announce Type: new Abstract: Rehabilitation exercises are essential in restoring lost physical functions of patients suffering from various diseases (e.g., Parkinson's, back pain).

arXiv:2606.28277v1 Announce Type: cross Abstract: Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem pr

arXiv:2606.27180v1 Announce Type: cross Abstract: Sparse rewards are inherently challenging for reinforcement learning agents as they lack intermediate feedback to guide exploration and to correctly a

arXiv:2606.24815v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are emerging robotic control systems that integrate perception, language understanding, and action generation in a

arXiv:2606.25178v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has been extended from single-domain training to multi-domain reasoning suites spanning mathematic

arXiv:2606.24589v1 Announce Type: new Abstract: Scaling adversarial evaluation of large language models requires both a method for generating hard inputs and a reliable way to confirm that resulting f

arXiv:2606.23032v2 Announce Type: replace Abstract: Finance Agent v2 (by Vals AI) has emerged as the reference benchmark for evaluating both Anthropic Claude and OpenAI ChatGPT frontier language model

arXiv:2606.22608v1 Announce Type: new Abstract: Learning to read cuneiform tablets is an extremely demanding task; consequently, of the roughly half million excavated tablets, only a small fraction ha

arXiv:2606.21116v1 Announce Type: new Abstract: Proofreading--correcting segmentation errors in 3D brain reconstructions--is the rate-limiting step in synapse-resolution connectomics. We release Conne

arXiv:2606.20642v1 Announce Type: cross Abstract: Asymptotic statistical theory is a challenging domain for AI-assisted formalization: its central results mix convergence statements, asymptotic expans

arXiv:2606.11459v1 Announce Type: cross Abstract: Large Language Models are highly sensitive to prompt formulation, necessitating automatic prompt optimization to unlock their full potential. While ev

arXiv:2606.12387v1 Announce Type: cross Abstract: Large Language Models (LLMs) have democratized database access through Text-to-SQL, but moving from prototypes to production remains difficult. Real d

arXiv:2606.11166v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly described as performing at the level of human experts on knowledge economy tasks. These claims are prima

arXiv:2512.18531v2 Announce Type: replace-cross Abstract: One-dimensional NMR spectroscopy is one of the most widely used techniques for the characterization of organic compounds and natural products.