Search: “automated”

arXiv:2609.35806v1 Announce Type: cross Abstract: Automated skill extraction underpins workforce planning, yet most systems represent skills as flat labels with no notion of the responsibility level a

arXiv:2609.27336v1 Announce Type: new Abstract: Automated red teaming often replays a fixed set of prompts, which measures known risks but cannot learn from failures found during testing. We present C

arXiv:2603.11667v3 Announce Type: replace Abstract: This paper examines how value is constructed and negotiated in today's increasingly automated language and translation industry. Drawing on intervie

arXiv:2609.14839v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into automated code optimization introduces a critical reliability risk we term the Efficiency Halluci

arXiv:2609.14770v1 Announce Type: cross Abstract: Generalisations are common in scientific communication, even though they are semantically ambiguous. An automated method is needed to identify and cat

arXiv:2609.14533v1 Announce Type: cross Abstract: Automated theorem proving seeks to use computational systems to prove or disprove mathematical and logical statements [1, 2]. It underpins a wide rang

arXiv:2609.12491v1 Announce Type: new Abstract: Skeleton-based action recognition can support automated tracking of physiotherapy exercises, particularly in remote rehabilitation settings where contin

arXiv:2609.10594v1 Announce Type: cross Abstract: Expert evaluation of jailbreak responses is costly and difficult to scale, so the community increasingly relies on automated evaluators to determine w

arXiv:2609.08256v1 Announce Type: cross Abstract: Automated red-team attacks and blue-team defenses for large language models (LLMs) are advancing quickly. However, attackers and defenders are built a

arXiv:2601.13591v3 Announce Type: replace Abstract: Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning. However, the open-ended nature of real-

arXiv:2609.10123v1 Announce Type: cross Abstract: Large language models (LLMs) have become ubiquitous in software development, with LLM-based automated program repair tools increasingly used during co

arXiv:2609.04439v1 Announce Type: new Abstract: Automated aortic segmentation in 4D flow MRI is essential for reproducible hemodynamic assessment but is limited by scarce dense annotations and high co

arXiv:2609.03463v1 Announce Type: new Abstract: Automated pig monitoring is essential for assessing their health, behaviour, and welfare. To date, most pig monitoring solutions operate on the group-le

arXiv:2412.14626v3 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have demonstrated their potential in automating the scientific research ideation. Existing

arXiv:2609.00682v1 Announce Type: new Abstract: Intelligent vehicles increasingly support adaptive applications beyond driving themselves, ranging from context-aware ADAS and automated driving to in-c

arXiv:2608.27923v1 Announce Type: new Abstract: Printed circuit boards (PCBs) are fundamental to modern electronic systems, yet AI-driven PCB design automation remains constrained by the lack of large

arXiv:2608.25570v1 Announce Type: new Abstract: Hardware kernel optimization requires repeated compilation, correctness testing, profiling, and revision. LLM agents can automate parts of this process,

arXiv:2608.25660v1 Announce Type: new Abstract: Automated novelty judgment can accelerate scientific discovery by enabling efficient evaluation, refinement, and comparison of research ideas. While lar

arXiv:2608.24793v1 Announce Type: new Abstract: Automated malaria diagnosis from stained blood-smear microscopy is dominated by deep convolutional neural networks that are accurate but computationally

arXiv:2608.23061v1 Announce Type: new Abstract: Background: Automating clinical guideline-based decision-making with large language models (LLMs) remains challenging because of reliability, hallucinat

arXiv:2608.18933v1 Announce Type: cross Abstract: Large language model (LLM) based agents have demonstrated remarkable proficiency in automated software issue resolution, yet they often struggle to re

arXiv:2608.17522v1 Announce Type: cross Abstract: Persistent shortages in the surgical workforce and inherent limitations of traditional training methods highlight the necessity of automated, data-dri

arXiv:2608.14720v1 Announce Type: cross Abstract: Following the molecular discovery and synthesis revolutions, scalable automated structure elucidation from routine spectroscopic data remains an outst

arXiv:2608.14407v1 Announce Type: new Abstract: We present a survey of the past and future of AI Scientists: machines capable of automating science. AI Scientists can originate hypotheses, deduce thei

arXiv:2608.07437v1 Announce Type: new Abstract: Reliable hypothesis testing is the foundation of many empirical scientific claims. Large language model (LLM) agents are increasingly used to automate t

arXiv:2608.02353v1 Announce Type: new Abstract: Recent advances in agentic workflow optimization automate workflow design through task-specific workflow search or input-conditioned architecture select

arXiv:2607.27671v1 Announce Type: new Abstract: The majority of the recently-developed models for automated essay scoring (AES) are evaluated solely on the ASAP corpus. However, ASAP is not without it

arXiv:2607.26068v1 Announce Type: cross Abstract: Existing AI governance frameworks, including the EU AI Act and NIST AI RMF, address safety, transparency, and accountability but do not operationalize

arXiv:2607.26998v1 Announce Type: cross Abstract: Large language model (LLM) agents automate penetration testing through an observation-action loop, selecting actions based on observations returned by

arXiv:2607.25911v1 Announce Type: cross Abstract: Annotation is among the most demanding visualization tasks to automate, as it simultaneously requires correctly navigating visual, semantic, and styli

arXiv:2607.20675v1 Announce Type: new Abstract: Machine learning (ML) models are increasingly integrated into optical network automation frameworks to support tasks such as failure management, perform

arXiv:2607.12605v1 Announce Type: cross Abstract: Large language models (LLMs) have improved automated program repair (APR), but two limitations remain. First, raw execution traces are often too large

arXiv:2607.03553v1 Announce Type: new Abstract: Automation in construction is essential for reducing costs and human errors in large-scale projects. We approach the construction progress monitoring fr

arXiv:2607.04378v1 Announce Type: new Abstract: Surgical automation is being increasingly studied, yet bridging visual scene understanding with autonomous action planning remains a fundamental challen

arXiv:2606.06516v1 Announce Type: cross Abstract: We advance a new probabilistic supervised learning approach that permits reliable, automated, and early individualised prediction of the severity with

arXiv:2606.05458v1 Announce Type: new Abstract: Automated detection of equine facial action units (AUs) is a promising yet under-explored avenue for pain and affective state assessment in horses. Half

arXiv:2606.00065v1 Announce Type: cross Abstract: Automated extraction of materials composition-property data from scientific literature has advanced considerably with the development of large languag

arXiv:2606.00708v1 Announce Type: new Abstract: Automated data science is a structured model-selection problem. A solution must choose data transformations, feature representations, architecture, trai

arXiv:2606.01901v1 Announce Type: cross Abstract: We introduce the Image Reconstruction Game, a fully automated benchmark in which a vision-language model issues corrective instructions to an image ge

arXiv:2605.29931v1 Announce Type: new Abstract: In this paper, we present the results of an ethnographic study into the impact of AI and automated tools on music production workflow. Focusing specific

arXiv:2605.28552v1 Announce Type: new Abstract: As automated vehicles (AVs) increasingly share roadways with human-driven vehicles (HDVs), understanding how pedestrians respond to different vehicle ty

arXiv:2605.24453v1 Announce Type: cross Abstract: Large Language Model (LLM)-based code analysis tools are adopted to automate software documentation tasks. However, the scalability of these approache

arXiv:2605.23118v1 Announce Type: cross Abstract: Tracking tumor lesions across serial CT scans is essential for oncological response assessment. Existing automated methods face a fundamental trade-of

arXiv:2510.16559v5 Announce Type: replace Abstract: Engineering construction automation aims to transform natural language specifications into physically viable structures, requiring complex integrate

arXiv:2605.17159v1 Announce Type: new Abstract: Document processing automation remains a critical challenge in enterprise environments, where traditional manual approaches are labor-intensive and erro

arXiv:2605.12981v1 Announce Type: cross Abstract: Automated program synthesis has reduced the cost of producing candidate implementations, but it introduces a harder governance problem: determining wh