Search: “automated”

Advanced Topic Modeling Techniques for Categorizing Software Vulnerabilities

arXiv:2607.03887v1 Announce Type: cross Abstract: The increasing complexity and frequency of software vulnerabilities demand efficient methods to analyze and prioritize threats. Traditional approaches

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Agentic Artificial Intelligence for Multistage Physics Experiments at a Large-Scale User Facility Particle Accelerator

DGX agent

arXiv:2509.17255v2 Announce Type: replace-cross Abstract: We present the first language-model-driven agentic artificial intelligence (AI) system to autonomously execute multi-stage physics experiments

safetyarxiv-cs-ai

7 Jul 2026

Autonomous Information Seeking: A Roadmap for Agentic Recommender Systems

arXiv:2607.04433v1 Announce Type: cross Abstract: The rapid integration of large language model-based agents into recommender systems has driven a shift from static, ranking-based pipelines toward aut

safetyarxiv-cs-cl

BoRP: Bootstrapped Regression Probing for Scalable and Human-Aligned LLM Evaluation

arXiv:2601.18253v2 Announce Type: replace-cross Abstract: Accurate evaluation of user satisfaction is critical for iterative development of conversational AI. However, for open-ended assistants, tradi

safetyarxiv-cs-ai

Agents

Builder, Defender, Breaker: The Case Against Removing the Human from the AI-Driven Security Lifecycle

arXiv:2607.03215v1 Announce Type: cross Abstract: Artificial intelligence has spread across the whole of the security lifecycle. The same family of models now writes application code, hardens it, and

agentsarxiv-cs-ai

Can temporal article-level credibility signals improve domain-level credibility prediction?

arXiv:2607.04560v1 Announce Type: new Abstract: Web domain credibility evaluation is vital for combating misinformation. It is conducted by examining factors such as domain type, transparency, and ove

safetyarxiv-cs-cl

CenSynCMB: Centre Maps and Physics-Guided Synthesis for Microbleed Detection

arXiv:2607.05325v1 Announce Type: new Abstract: Cerebral microbleeds (CMBs) are MRI markers of small vessel disease and the microbleed component of amyloid related imaging abnormalities (ARIA-H), but

Applications

Classroom Behavior Monitoring with YOLO An Empirical Study in Higher Education Settings

arXiv:2607.02580v1 Announce Type: new Abstract: Classroom behavior monitoring plays a vital role in evaluating student engagement and improving teaching effectiveness. Traditional observation methods

applicationsarxiv-cs-cv

Comparison of Loss Functions for Robust Deep Learning-based Echocardiography Segmentation when Learning with Partially Labelled Data from Multiple Domains

arXiv:2607.05008v1 Announce Type: cross Abstract: Echocardiography is the first imaging modality used for assessing cardiac function, and accurate segmentation of cardiac structures is essential for d

CONTRA: Red-Teaming Configurations of Personalizable Agents

arXiv:2607.03220v1 Announce Type: cross Abstract: Recent tools such as OpenClaw have extended the capabilities of LLM-based agents from simple dialog-based systems to fully autonomous agents. These sy

safetyarxiv-cs-ai

Local Ai

CORA: Generalizable coronary artery disease assessment and risk stratification from coronary CT angiography using pathology-centric representation learning

arXiv:2603.24847v2 Announce Type: replace Abstract: Coronary artery disease, a leading cause of cardiovascular mortality worldwide, can be assessed non-invasively by coronary computed tomography angio

local-aiarxiv-cs-cv

Cross-Modal Fusion of OCT and OCT angiography enface for Improved Diagnostics of Diabetic Retinopathy

arXiv:2607.03959v1 Announce Type: cross Abstract: Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, highlighting the need for accurate and accessible screening tools. Optica

Dashboard2Code: Evaluating Multimodal Models on Reconstructing Interactive Dashboards

arXiv:2607.04727v1 Announce Type: cross Abstract: Automatic data visualization generation has advanced rapidly with multi-modal large language models, yet existing efforts largely focus on static char

Tutorials

Diagnosing Aerial-View Object Detectors with Foundational Image Generative Models

arXiv:2607.02718v1 Announce Type: cross Abstract: Recent advances in large-scale image generative models enable photorealistic scene synthesis with controllable attributes. Beyond data augmentation, t

tutorialsarxiv-cs-ai

DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections

arXiv:2508.12116v2 Announce Type: replace-cross Abstract: As numerous instruction-tuning datasets continue to emerge, dynamically balancing and optimizing their mixtures has become a critical challeng

EM3M: An Electron Micrograph Dataset for Microstructural Segmentation and Generation

arXiv:2508.16239v2 Announce Type: replace Abstract: Quantitative microstructural characterization is fundamental to materials science, and electron micrographs (EMs) provide indispensable high-resolut

Evaluating Intellectual Property Guardrails of Generative Image Models: A Technical Report

arXiv:2607.02582v1 Announce Type: new Abstract: Generative image models are capable of producing images that bear a strong resemblance to, or replicate, recognizable intellectual property (IP). In thi

FormalRx: Rectify and eXamine Semantic Failures in Autoformalization

model-releasesarxiv-cs-cl

arXiv:2607.04655v1 Announce Type: new Abstract: The veracious semantic alignment in autoformalization is significant for formal mathematical reasoning. However, existing evaluations provide only opaqu

Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling

arXiv:2604.14221v2 Announce Type: replace Abstract: Reliable evaluation of anomaly detection methods in multivariate time series remains an open challenge, largely due to the limitations of existing b

GLOW-FDG: Generalized cancer LesiOn Whole-body segmentation model for ^{18}F-FDG-PET/CT

arXiv:2607.03931v1 Announce Type: cross Abstract: Whole-body fluorodeoxyglucose positron emission tomography combined with computed tomography is widely used in cancer care, but manual lesion delineat

Local Ai

GRCD: Grounded Region Change Detection for Multi-Finding Chest X-Ray Pairs

arXiv:2607.02719v1 Announce Type: new Abstract: Radiologists routinely compare current and prior chest X-rays to track disease progression, producing follow-up reports that describe multiple findings,

local-aiarxiv-cs-cv

Individual Parameters in Weight-Sparse Transformers Appear Interpretable

arXiv:2607.02964v1 Announce Type: cross Abstract: A central goal of mechanistic interpretability is to understand how neural networks work and what each individual component does. Dominant circuit-fin

Local Ai

Internal Pluralism and the Limits of Pairwise Comparisons

arXiv:2607.02672v1 Announce Type: new Abstract: Local pairwise comparisons are a standard tool for learning how people want decision rules to work, e.g., in participatory design or alignment. However,

local-aiarxiv-cs-ai

IRG-MotionLLM: Interleaving Motion Generation, Assessment and Refinement for Text-to-Motion Generation

arXiv:2512.10730v2 Announce Type: replace Abstract: Recent advances in motion-aware large language models have shown remarkable promise for jointly learning motion understanding and generation knowled

LeukocyteCount: Automatic Identification and Counting for leukocytes using Deep Learning

arXiv:2607.04486v1 Announce Type: cross Abstract: Diagnosing and monitoring diseases frequently involves the analysis of human biological samples, with blood analysis being pivotal. Specifically, leuk

Medi-Gemma: A Hybrid Clinical Decision Support System Integrating Deterministic EMR Analytics and Retrieval-Augmented Generation

arXiv:2607.04907v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in high-stakes clinical settings remains limited by structural hallucinations, weak deterministic reasoning over

NKI-Agent: Domain-Specific Fine-Tuning and Agentic Tool Use for Neuron Kernel Generation

model-releasesarxiv-cs-lg

arXiv:2607.04395v1 Announce Type: new Abstract: Recent agentic approaches to LLM-based kernel generation have achieved impressive results on CUDA. For emerging AI accelerators such as AWS Trainium and

OmniLayout: A Schematic-Coupled Multimodal Benchmark for Constraint-Aware Geometric Reasoning in PCB Layout

arXiv:2607.03261v1 Announce Type: new Abstract: Recent large language models (LLMs) have demonstrated remarkable progress in 3D spatial reasoning, spatial grounding, and fine-grained geometric underst

PhenoNEST: A Neuro-Symbolic Framework for Ontology-Aware Multimodal Plant Phenotyping and Trait Discovery

arXiv:2607.03245v1 Announce Type: new Abstract: High-throughput plant phenotyping generates valuable data that often remains trapped in unstructured text and isolated RGB images. To bridge this semant

researcharxiv-cs-lg

PhysMirror: Physics-Aware Mirror Object Generation

arXiv:2607.03470v1 Announce Type: new Abstract: Synthesizing physically accurate mirror reflections remains a fundamental challenge for modern text-to-image diffusion models, which are increasingly cr

Probe-EM: Targeted Neuron Tracing via Training-Free Semantic Verification

arXiv:2607.04696v1 Announce Type: new Abstract: Establishing large-scale, high-resolution neural connectivity maps is fundamental to elucidating the structural basis of brain function. However, when p

ResearchStudio-Idea: An Evidence-Grounded Research-Ideation Skill Suite from ML Conference Outcomes

arXiv:2607.04439v1 Announce Type: new Abstract: Large language models have made research ideation increasingly accessible, yet effective idea development requires more than generating candidate direct

Agents

Robustness Verification of an Autonomous Underwater Vehicle-based Plankton Classifier

arXiv:2607.04453v1 Announce Type: cross Abstract: The assessment of planktonic standing stocks and microorganism structures is critical for understanding upper ocean biological processes. Currently, a

agentsarxiv-cs-ai

Semantic Segmentation-Driven Image-Level Diagnosis of Liver Cancers in Hematoxylin and Eosin Histopathology Images

arXiv:2607.03253v1 Announce Type: cross Abstract: As hematoxylin & eosin (H&E) staining constitutes the primary entry point in routine diagnostic workflows, computer-aided diagnosis from whole-slide H

SIMPLER: Efficient Foundation Model Adaptation via Similarity-Guided Layer Pruning for Earth Observation

arXiv:2603.19873v2 Announce Type: replace Abstract: Fine-tuning foundation models for Earth Observation is computationally expensive, with high training time and memory demands for both training and d

SMART: A Machine Learning and Monte Carlo Framework for Rapid Analysis of Stochastic Transistor Aging and Process Variation in Digital Circuits

model-releasesarxiv-cs-lg

arXiv:2607.05187v1 Announce Type: new Abstract: As CMOS technology scales into the deep nanometer regime, digital circuit reliability is increasingly threatened by the combined stochastic effects of B

SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses

arXiv:2510.15476v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used as interfaces to information, code, and real-world services, making prompt-level security f

safetyarxiv-cs-ai

Agents

TAMA: A Human-AI Collaborative Thematic Analysis Framework Using Multi-Agent LLMs for Clinical Interviews

arXiv:2503.20666v2 Announce Type: replace-cross Abstract: Thematic analysis (TA) is a widely used qualitative approach for uncovering latent meanings in unstructured text data. TA provides valuable in

agentsarxiv-cs-cl

Taming I2V models for Image HOI Editing: A Cognitive Benchmark and Agentic Self-Correcting Framework

arXiv:2606.19073v2 Announce Type: replace Abstract: Current image editing methods excel at static attributes but fail at complex Human-Object Interactions (HOI), a critical challenge unaddressed by ex

Tracing 3D Anatomy in 2D Strokes: A Multi-Stage Projection Driven Approach to Cervical Spine Fracture Identification

arXiv:2601.15235v4 Announce Type: replace-cross Abstract: Cervical spine fractures require rapid and accurate diagnosis, yet automatic CT interpretation remains challenging as subtle injuries must be

TRIAGE: Trustworthy Retrieval Instrumentation And Graph Evaluation

arXiv:2607.03447v1 Announce Type: cross Abstract: Knowledge graphs (KGs) that underpin Graph-based Retrieval-Augmented Generation (Graph-RAG) are increasingly built automatically by LLM-driven extract

VERITAS: Towards a General-Purpose Replication Tool for Scientific Research

arXiv:2607.02931v1 Announce Type: new Abstract: AI tools are accelerating scientific publication while the systems that review it struggle to keep up, and independent verification of published researc

Video-based detection of cessation of breathing in pre-term infants using machine learning

arXiv:2607.05230v1 Announce Type: new Abstract: Pre-term infants are susceptible to potentially harmful apnoea-related cessations of breathing due to immature respiratory control. However, reliable re

researcharxiv-cs-lg

Applications

VLMGuard: Bootstrapping Malicious Prompt Detectors from Unlabeled Vision-Language Prompts in the Wild

arXiv:2410.00296v2 Announce Type: replace Abstract: Vision-language Models (VLMs) are essential for contextual understanding of both visual and textual information. However, their vulnerability to adv

applicationsarxiv-cs-lg

Wavelet Scattering Transform for Interpretable Schizophrenia Biomarker Discovery and Classification from Resting-State EEG

arXiv:2607.05282v1 Announce Type: cross Abstract: Schizophrenia is a debilitating neuropsychiatric disorder characterized by profound cortical network dysregulation, for which objective, clinically tr

Applications

What is Left for Us? Second Scholarship Against the Degradation of Research by AI

arXiv:2607.04049v1 Announce Type: new Abstract: We argue that generative AI can degrade research by eroding the very practices through which scholarly judgement is formed and academic trust is built.

applicationsarxiv-cs-ai

When Do Foundation Models Pay Off? A Break-Even Analysis of Pretrained Time Series Forecasters

model-releasesarxiv-cs-lg

arXiv:2607.04919v1 Announce Type: new Abstract: Deploying a time series foundation model requires GPU infrastructure, engineering overhead, and carries no guarantee of improvement over XGBoost. We pro

Tutorials

ADVENT: LLM-Driven Automatic Predicate Invention for ILP