Search: “automated”

arXiv:2507.10614v2 Announce Type: replace-cross Abstract: The integration of large language models (LLMs) into automated algorithm design has shown promising potential. A prevalent approach embeds LLM

arXiv:2603.22453v2 Announce Type: replace Abstract: Community Notes have emerged as an effective crowd-sourced mechanism for combating online deception on social media platforms. However, its reliance

arXiv:2605.17937v1 Announce Type: cross Abstract: Quantitative backtesting is essential for evaluating trading strategies but remains hampered by high technical barriers and limited scalability. While

arXiv:2504.07738v3 Announce Type: replace Abstract: In this document, we discuss a multi-step approach to automated construction of a knowledge graph, for structuring and representing domain-specific

arXiv:2605.13539v1 Announce Type: new Abstract: Simulative and scenario-based testing are crucial methods in the safety assurance for automated driving systems. To ensure that simulation results are r

arXiv:2605.09350v1 Announce Type: new Abstract: Smart-contract exploits have caused billions of USD in cumulative losses, yet audits remain expensive and slow. Automated tools have emerged to close th

arXiv:2605.10327v1 Announce Type: cross Abstract: In this paper, we present SCALAR (Symbolic Conjecture and LLM-Assisted Reasoning), a neurosymbolic framework for automated conjecture generation in qu

arXiv:2605.05775v2 Announce Type: replace-cross Abstract: We report the design and results of the third autoPET challenge (MICCAI 2024), which benchmarked automated lesion segmentation in whole-body P

arXiv:2605.07647v1 Announce Type: cross Abstract: Automated short answer scoring (ASAS) is shifting from discriminative, fine-tuned models to large language models (LLMs) used in few-shot settings. Th

arXiv:2605.04472v1 Announce Type: new Abstract: Automating formal proofs of combinatorial identities is challenging for LLM-based provers, as long-horizon proof planning is required and unconstrained

arXiv:2605.03212v1 Announce Type: cross Abstract: Modeling latent clinical constructs from unconstrained clinical interactions is a unique challenge in affective computing. We present ADAPTS (Agentic

arXiv:2605.01555v1 Announce Type: new Abstract: We introduce an autonomous multiagent framework for mechanistic interpretability that automates both explaining and finding internal features in large l

arXiv:2410.08491v2 Announce Type: replace Abstract: Automated vehicles promise to enhance transportation safety and efficiency. However, ensuring their reliability in real-world conditions remains cha

arXiv:2604.26954v1 Announce Type: cross Abstract: Strategic model selection and reasoning settings are more effective than ensembling for optimizing automated scoring with large language models (LLMs)

arXiv:2604.27685v1 Announce Type: cross Abstract: While machine-learned interatomic potentials (MLIPs) accelerate phonon dispersion calculations, merely identifying dynamical instabilities in computat

arXiv:2507.06803v3 Announce Type: replace-cross Abstract: This paper contributes to speeding up the design and deployment of engineering dynamical systems by proposing a strategy for exploiting domain

arXiv:2604.20374v1 Announce Type: new Abstract: Automated Market Makers (AMMs), as a core infrastructure of decentralized finance (DeFi), uniquely drive on-chain asset pricing through a deterministic

arXiv:2604.19131v1 Announce Type: new Abstract: Automated essay scoring (AES) is commonly evaluated on public benchmarks using quadratic weighted kappa (QWK). However, because benchmark labels are ass

arXiv:2604.18976v1 Announce Type: new Abstract: While Large Language Models (LLMs) are widely used, they remain susceptible to jailbreak prompts that can elicit harmful or inappropriate responses. Thi

arXiv:2604.15589v1 Announce Type: cross Abstract: Existing research on large language models (LLMs) for automated code compliance has primarily focused on performance, treating the models as black box

arXiv:2505.10846v3 Announce Type: replace Abstract: This paper presents AutoRAN, the first framework to automate the hijacking of internal safety reasoning in large reasoning models (LRMs). At its cor

arXiv:2604.15224v1 Announce Type: cross Abstract: The extit{LLM-as-a-judge} paradigm has become the operational backbone of automated AI evaluation pipelines, yet rests on an unverified assumption: th

arXiv:2403.10559v3 Announce Type: replace Abstract: This report investigates the history and impact of Generative Models and Connected and Automated Vehicles (CAVs), two groundbreaking forces pushing

arXiv:2604.13891v1 Announce Type: new Abstract: Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need to balance safety and efficiency.

arXiv:2603.13941v2 Announce Type: replace Abstract: Growing waste streams and the transition to a circular economy require efficient automated waste sorting. In industrial settings, materials move on

arXiv:2604.09815v1 Announce Type: new Abstract: Computer-use agents that combine GUI interaction with structured API calls via the Model Context Protocol (MCP) show promise for automating software tas

arXiv:2511.08659v3 Announce Type: replace-cross Abstract: This book is an introductory textbook targeted towards computer science students who are completely new to the topic of automated negotiation.

arXiv:2604.10740v1 Announce Type: new Abstract: Despite the widespread adoption of Large Language Models (LLMs) in Legal AI, their utility for automated contract revision remains impeded by hallucinat

arXiv:2604.11655v1 Announce Type: cross Abstract: The rapid adoption of Large Language Models (LLMs) in interactive systems has enabled the creation of dynamic, open-ended Role-Playing Agents (RPAs).

arXiv:2604.08610v1 Announce Type: new Abstract: This paper presents a semi-automated framework for transforming two-dimensional miniatures from medieval manuscripts into three-dimensional digital mode

arXiv:2604.09166v1 Announce Type: new Abstract: Anomaly detection (AD) in chemical processes based on deep learning offers significant opportunities but requires large, diverse, and well-annotated tra

arXiv:2604.09418v1 Announce Type: new Abstract: This paper studies Automated Instruction Revision (AIR), a rule-induction-based method for adapting large language models (LLMs) to downstream tasks usi

arXiv:2604.09111v1 Announce Type: cross Abstract: Recently, artificial intelligence-based dubbing technology has advanced, enabling automated dubbing (AD) to convert the source speech of a video into

arXiv:2604.08578v1 Announce Type: cross Abstract: High-quality labeled data is critical for training reliable machine learning and deep learning models, yet manual annotation remains costly and error-

arXiv:2604.09047v1 Announce Type: new Abstract: Dental implant abutments serve as the geometric and biomechanical interface between the implant fixture and the prosthetic crown, yet their design relie

arXiv:2604.07780v1 Announce Type: cross Abstract: Objective: To develop a robust and compact deep learning model for automated knee cartilage segmentation on point-of-care ultrasound (POCUS) devices.

arXiv:2610.09769v1 Announce Type: cross Abstract: Large language models are increasingly contributing to mathematical research, where progress often depends on efficient proof search, incremental impr

arXiv:2610.07502v1 Announce Type: new Abstract: Provider queries are clarifying requests sent by clinical documentation specialists to physicians to close gaps in the clinical note and ensure accurate

arXiv:2610.07132v1 Announce Type: cross Abstract: Croissant has emerged as a standard for machine-readable dataset metadata, yet populating its fields remains labor-intensive and requires careful read

arXiv:2610.03505v1 Announce Type: new Abstract: Post-exposure microscopy is central to qualification of fusion materials. However, manual analysis does not scale to the volume, heterogeneity, and mult

arXiv:2610.03383v1 Announce Type: new Abstract: Attack Path (AP) modeling is fundamental to cybersecurity analysis, where the Planning Domain Definition Language (PDDL) has been widely adopted to enco

arXiv:2609.35812v1 Announce Type: new Abstract: In-car conversational assistants (ICAs) are increasingly integrated into vehicles to support route planning, vehicle control, and information access. En

arXiv:2601.08701v2 Announce Type: replace-cross Abstract: Accurate and generalisable segmentation of stroke lesions from magnetic resonance imaging (MRI) is essential for advancing clinical research,

arXiv:2609.30796v1 Announce Type: new Abstract: Diagnostic consultation is an online sequential decision-making process in which clinicians gather evidence through patient interaction until a diagnosi

arXiv:2601.01842v2 Announce Type: replace Abstract: Dictionary definitions are an essential resource for learning word senses, but manually creating them is costly. We thus study dictionary definition

arXiv:2609.30107v1 Announce Type: new Abstract: Smartphone cameras and computer vision (CV) hold significant promise in assisting public agencies with enforcing traffic laws and enhancing road safety.