Search: “automated”

HeartBeatAI: An Interpretable and Robust Deep Learning Framework for Multi-Label ECG Arrhythmia Detection

arXiv:2605.24588v1 Announce Type: new Abstract: While Deep Learning (DL) enhances automated electrocardiogram (ECG) analysis, clinical deployment is hindered by class imbalance and the generalization

researcharxiv-cs-ai

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Safety

Improving Labeling Consistency with Detailed Constitutional Definitions and AI-Driven Evaluation

DGX agent

arXiv:2605.24247v1 Announce Type: cross Abstract: Many automated labeling pipelines classify inputs into categories defined by a written specification, content moderation being a prominent use case. S

safetyarxiv-cs-ai

26 May 2026

Applications

In Search of the Ingredients of Open-Endedness: Replicating Picbreeder with Large Vision-Language Models

arXiv:2605.23908v1 Announce Type: new Abstract: We are in the midst of large-scale industrial and academic efforts to automate the processes of scientific, technological and creative production throug

applicationsarxiv-cs-ai

Keep the Proof State Live: Snapshotting for Efficient Tactic Search in Lean 4

arXiv:2605.25556v1 Announce Type: cross Abstract: Automated theorem proving systems built on Lean 4 increasingly rely on parallel tactic search over partially specified proofs, such as those generated

ROC Analysis for Evaluating Translation Quality Estimation Systems

arXiv:2605.24721v1 Announce Type: new Abstract: The increasing use of automated translation quality estimation (QE) systems calls for practical, decision-oriented methods for evaluating their performa

researcharxiv-cs-cl

A Novel Approach for the Counting of Wood Logs Using cGANs and Image Processing Techniques

arXiv:2605.23775v1 Announce Type: new Abstract: This study tackles the challenge of precise wood log counting, where applications of the proposed methodology can span from automated approaches for mat

safetyarxiv-cs-cv

Agentic Proving for Program Verification

arXiv:2605.23772v1 Announce Type: new Abstract: Agentic systems have recently emerged as state-of-the-art approaches for automated theorem proving in formal mathematics. To assess how far these capabi

Ax-Prover: A Deep Reasoning Agentic Framework for Theorem Proving in Mathematics and Quantum Physics

arXiv:2510.12787v4 Announce Type: replace Abstract: We present Ax-Prover, a multi-agent system for automated theorem proving in Lean that can solve problems across diverse scientific domains and opera

Tutorials

Nonlinear Transformations Against Unlearnable Datasets

arXiv:2406.02883v2 Announce Type: replace Abstract: Automated scraping stands out as a common method for collecting data in deep learning models without the authorization of data owners. Recent studie

tutorialsarxiv-cs-lg

Online Learning with Multiple Fairness Regularizers via Graph-Structured Feedback

arXiv:2508.14311v2 Announce Type: replace-cross Abstract: There is an increasing need to enforce multiple, often competing, measures of fairness within automated decision systems. The appropriate weig

Reinforcement Learning with Verifiable yet Noisy Rewards under Imperfect Verifiers

arXiv:2510.00915v4 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) replaces costly human labeling with automated verifiers. To reduce verifier hacking, man

RMA: an Agentic System for Research-Level Mathematical Problems

arXiv:2605.22875v1 Announce Type: new Abstract: We present extbf{Research Math Agents (RMA)}, an agentic framework for automated reasoning on research-level mathematical problems. Unlike prior studies

Staging by the Book: Automatic Sleep Stage Classification Using Scoring Rules

arXiv:2605.22859v1 Announce Type: cross Abstract: Automated sleep staging is commonly approached as a supervised machine learning problem, with deep learning methods dominating recent research. While

researcharxiv-cs-ai

CoFEH: LLM-driven Feature Engineering Empowered by Collaborative Bayesian Hyperparameter Optimization

arXiv:2602.09851v2 Announce Type: replace Abstract: Feature Engineering (FE) is pivotal in automated machine learning (AutoML) but remains a bottleneck for traditional methods, which operate within ri

researcharxiv-cs-lg

23 May 2026

A Task-Agnostic Algebraic Integrity Metric for Event-Camera Streams Toward SOTIF-Compliant Perception using Pearson Correlation Coefficient

model-releasesarxiv-cs-cv

arXiv:2605.21500v1 Announce Type: cross Abstract: Event cameras have emerged as a high-bandwidth, low-latency sensing modality for safety-critical perception in automated driving systems (ADS), offeri

AMEL: Accumulated Message Effects on LLM Judgments

arXiv:2605.22714v1 Announce Type: cross Abstract: Large language models are routinely used as automated evaluators: to review code, moderate content, or score outputs, often with many items passing th

From Recognition to Reasoning: Benchmarking and Enhancing MLLMs on Real-World Receipt Document Understanding

model-releasesarxiv-cs-cv

arXiv:2605.22413v1 Announce Type: new Abstract: Extracting structured information from visual documents (Visual Information Extraction, VIE) is a cornerstone of business automation. While recent Multi

Revisiting Integration of Image and Metadata for DICOM Series Classification: Cross-Attention and Dictionary Learning

arXiv:2602.23833v2 Announce Type: replace-cross Abstract: Automated identification of DICOM image series is essential for large-scale medical image analysis, quality control, protocol harmonization, a

researcharxiv-cs-cv

Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation

arXiv:2605.21491v1 Announce Type: cross Abstract: As language models accelerate scientific research by automating hypothesis generation and implementation, a new bottleneck emerges: evaluating and fil

Agents

Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling

arXiv:2605.21470v1 Announce Type: new Abstract: Computer-use agents (CUA) automate tasks specified with natural language such as 'order the cheapest item from Taco Bell' by generating sequences of cal

agentsarxiv-cs-lg

Tutorials

Building a Custom Taxonomy of AI Skills and Tasks from the Ground Up with Job Postings

arXiv:2605.21029v1 Announce Type: new Abstract: Utilizing LLMs for automated taxonomy construction presents a clear opportunity for the comprehensive, yet efficient mapping of potentially complex doma

tutorialsarxiv-cs-cl

Component Influence-Driven Fastener Reduction for Robotic Disassemblability-Aware Design Simplification

arXiv:2605.21026v1 Announce Type: new Abstract: To accelerate automated remanufacturing, robotic disassembly must be considered during the product design phase. However, designers currently lack quant

researcharxiv-cs-ro

Domain-Adaptable Reinforcement Learning for Code Generation with Dense Rewards

arXiv:2605.21180v1 Announce Type: new Abstract: Large language models show strong potential for automated code generation, but lack guarantees for correctness, quality, safety, and domain-specific con

safetyarxiv-cs-lg

ECUAS{n}: A family of metrics for principled evaluation of uncertainty-augmented systems

model-releasesarxiv-cs-lg

arXiv:2605.20490v1 Announce Type: cross Abstract: In high-stakes automated decision-making, access to predictive uncertainty is essential for enabling users -- human or downstream systems -- to accept

FineVision: Open Data Is All You Need

arXiv:2510.17269v2 Announce Type: replace Abstract: The advancement of vision-language models (VLMs) is hampered by a fragmented landscape of inconsistent and contaminated public datasets. We introduc

safetyarxiv-cs-cv

Online 3D Multi-Camera Perception through Robust 2D Tracking and Depth-based Late Aggregation

arXiv:2509.09946v2 Announce Type: replace Abstract: Multi-Target Multi-Camera Tracking (MTMC) is an essential computer vision task for automating large-scale surveillance. With camera calibration and

local-aiarxiv-cs-cv

Agents

Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches

arXiv:2510.04905v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have significantly improved automated code generation. While existing approaches have achieved

agentsarxiv-cs-cl

SpecBench: Measuring Reward Hacking in Long-Horizon Coding Agents

arXiv:2605.21384v1 Announce Type: cross Abstract: As long-horizon coding agents produce more code than any developer can review, oversight collapses onto a single surface: the automated test suite. Re

SpineContextResUNet: A Computationally Efficient Residual UNet for Spine CT Segmentation

arXiv:2605.20760v1 Announce Type: new Abstract: Automated segmentation of the vertebral column in Computed Tomography (CT) scans is a prerequisite for pathological assessment and surgical planning. Ho

local-aiarxiv-cs-cv

Agents

SubTGraph: Large-Scale Subterranean Environment Synthesis with Controllable Topological Variability for Robotic Autonomy Validation

arXiv:2605.20917v1 Announce Type: new Abstract: Subterranean (SubT) environments have been a frontier for autonomous robotics, driven by the push for automation of mining operations and the interest i

agentsarxiv-cs-ro

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration

arXiv:2605.20025v1 Announce Type: new Abstract: Automating scientific discovery requires more than generating papers from ideas. Real research is iterative: hypotheses are challenged from multiple per

CaptchaMind: Training CAPTCHA Solvers via Reinforcement Learning with Explicit Reasoning Supervision

arXiv:2605.19538v1 Announce Type: cross Abstract: CAPTCHAs are widely deployed as human verification mechanisms and frequently block intelligent agents from completing end-to-end automation in real-wo

Generative Auto-Bidding with Unified Modeling and Exploration

arXiv:2605.19457v1 Announce Type: new Abstract: Automated bidding is central to modern digital advertising. Early rule-based methods lacked adaptability, while subsequent Reinforcement Learning approa

GRASP: Deterministic argument ranking in interaction graphs

arXiv:2605.19141v1 Announce Type: cross Abstract: Large language models are increasingly deployed as automated judges to evaluate the strength of arguments. As this role expands, their legitimacy depe

local-aiarxiv-cs-ai

Mask-to-Correct^+: Leveraging Retriever Diversity for Masking-guided Faithful Fact Correction

arXiv:2605.18776v1 Announce Type: cross Abstract: The rapid spread of misinformation on social media highlights the need for robust, automated fact correction frameworks. However, existing works rely

Progressive Autonomy as Preference Learning: A Formalization of Trust Calibration for Agentic Tool Use

arXiv:2605.19151v1 Announce Type: new Abstract: We formalize trust calibration for agentic tool use (deciding when an automated agent's proposed action may execute autonomously versus require human ap

Qayyem: A Real-time Platform for Scoring Proficiency of Arabic Essays

arXiv:2603.01009v2 Announce Type: replace Abstract: Over the past years, Automated Essay Scoring (AES) systems have gained increasing attention as scalable and consistent solutions for assessing the p

researcharxiv-cs-cl

Time to REFLECT: Can We Trust LLM Judges for Evidence-based Research Agents?

arXiv:2605.19196v1 Announce Type: new Abstract: Deep research agents increasingly automate complex information-seeking tasks, producing evidence-grounded reports via multi-step reasoning, tool use, an

Towards Consistent Detection of Cognitive Distortions: LLM-Based Annotation and Dataset-Agnostic Evaluation

arXiv:2511.01482v2 Announce Type: replace Abstract: Text-based automated Cognitive Distortion detection is a challenging task due to its subjective nature, with low agreement scores observed even amon

Whispers of Wealth: Red-Teaming Google's Agent Payments Protocol via Prompt Injection

arXiv:2601.22569v2 Announce Type: replace-cross Abstract: Large language model (LLM) based agents are increasingly used to automate financial transactions, yet their reliance on contextual reasoning e

A-ProS: Towards Reliable Autonomous Programming Through Multi-Model Feedback

arXiv:2605.18073v1 Announce Type: cross Abstract: Large Language Models (LLMs) demonstrate strong potential for automated code generation, yet their ability to iteratively refine solutions using execu

Auditing Multimodal LLM Raters: Central Tendency Bias in Clinical Ordinal Scoring

model-releasesarxiv-cs-cv

arXiv:2605.16386v1 Announce Type: new Abstract: Multimodal large language models (LLMs) are increasingly explored as automated evaluators in clinical settings, yet their scoring behavior on ordinal cl

Augmenting Human Evaluation with LLM Judges: How Many Human Reviews Do You Need?

arXiv:2605.16354v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as automated evaluators of AI systems, including in high-stakes applications. In this role, LLMs ar

AutoVecCoder: Teaching LLMs to Generate Explicitly Vectorized Code

arXiv:2605.17978v1 Announce Type: new Abstract: Vectorization via Single Instruction, Multiple Data (SIMD) architectures is a cornerstone of high-performance computing. To fully exploit hardware poten

researcharxiv-cs-cl

Beyond Patches: Global-aware Autoregressive Model for Multimodal Few-Shot Font Generation

arXiv:2601.01593v2 Announce Type: replace Abstract: Manual font design is an intricate process that transforms a stylistic visual concept into a coherent glyph set. This challenge persists in automate

researcharxiv-cs-cv

BLAgent: Agentic RAG for File-Level Bug Localization

arXiv:2605.17965v1 Announce Type: cross Abstract: Bug localization remains a key bottleneck in downstream software maintenance tasks, including root cause analysis, triage, and automated program repai

local-aiarxiv-cs-ai

Tutorials

CoLLM-NAS: Collaborative Large Language Models for Efficient Knowledge-Guided Neural Architecture Search

arXiv:2509.26037v2 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) with Neural Architecture Search (NAS) has introduced new possibilities for automating the design of

tutorialsarxiv-cs-ai

ContraFix: Agentic Vulnerability Repair via Differential Runtime Evidence and Skill Reuse

arXiv:2605.17450v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly used for automated vulnerability repair (AVR), where repository-level reasoning enables them to ins