Search: “automated”

Creation of the Estonian Subjectivity Dataset: Assessing the Degree of Subjectivity on a Scale

model-releasesarxiv-cs-cl

arXiv:2512.09634v2 Announce Type: replace Abstract: This article presents the creation of an Estonian-language dataset for document-level subjectivity, analyzes the resulting annotations, and reports

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Database Normalization via Dual-LLM Self-Refinement

DGX agent

arXiv:2508.17693v2 Announce Type: replace-cross Abstract: Database normalization is crucial to preserving data integrity. However, it is time-consuming and error-prone, as it is typically performed ma

tutorialsarxiv-cs-ai

8 Jun 2026

DEFINED: A Data-Efficient Computational Framework for Fine-Grained Creativity Assessment in Debate Scenarios

arXiv:2606.07226v1 Announce Type: cross Abstract: Human creativity has emerged as a critical competency in the era of large language models. Assessing creativity in complex, open-ended environments is

safetyarxiv-cs-ai

Direct 3D-Aware Object Insertion via Decomposed Visual Proxies

arXiv:2606.06601v1 Announce Type: cross Abstract: Object insertion aims to seamlessly composite a reference object into a specified region of a background image. Recent diffusion-based methods achieve

researcharxiv-cs-ai

Discovering Multiscale Deep Formulas in Complex Systems via Neural-Guided Lambda Calculus

arXiv:2606.07426v1 Announce Type: new Abstract: A fundamental problem in science is identifying underlying patterns of complex systems in the form of concise mathematical formulas. Current Artificial

researcharxiv-cs-lg

Evaluating AI-based Scientific Knowledge Synthesis with Epidemiological Systematic Reviews

arXiv:2603.22327v2 Announce Type: replace-cross Abstract: Systematic literature reviews (SLRs) are a demanding and high-stakes form of scientific knowledge synthesis that remains underspecified as an

safetyarxiv-cs-ai

Evidence-Based Intelligent Diagnostic and Therapeutic Visualization System with Large Language Models: Multi-Turn Interaction and Multimodal Treatment Plan Generation

arXiv:2606.06869v1 Announce Type: new Abstract: Aim: Existing AI-assisted traditional Chinese medicine diagnostic tools suffer from opaque reasoning processes, passive interaction, and limited treatme

Feasible Action Space Reduction for Quantifying Causal Responsibility in Continuous Spatial Interactions

arXiv:2505.17739v2 Announce Type: replace-cross Abstract: Understanding the causal influence of one agent on another agent is crucial for safely deploying artificially intelligent systems such as auto

agentsarxiv-cs-ro

GlucoFM-Bench: Benchmarking Time-Series Foundation Models for Blood Glucose Forecasting

model-releasesarxiv-cs-lg

arXiv:2606.06881v1 Announce Type: new Abstract: Blood glucose forecasting models are foundational for modern diabetes management systems, as reliable short-term predictions can enable proactive interv

Interpretable factorization of clinical questionnaires to identify latent factors of psychopathology

arXiv:2312.07762v3 Announce Type: replace Abstract: Psychiatry research seeks to understand the manifestations of psychopathology in behavior, as measured in questionnaire data, by identifying a small

researcharxiv-cs-lg

MVSegNet: A Lightweight Boundary-Aware Network for Fetal Lateral Ventricle Segmentation and Atrial Width Estimation in Prenatal Ultrasound

arXiv:2606.06958v1 Announce Type: new Abstract: Fetal ventriculomegaly is assessed by measuring the atrial width of the lateral ventricle in prenatal ultrasound. Accurate segmentation is essential for

hardwarearxiv-cs-cv

OpenSkill: Open-World Self-Evolution for LLM Agents

arXiv:2606.06741v1 Announce Type: new Abstract: Self-evolving agents requires adaptation after deployment, but existing approaches assume a usable learning loop, such as curated skills, successful tra

agentsarxiv-cs-ai

PhyRoGen: Synthetic Generation of Physical Robot Manipulation Puzzles Using Procedural Content Generation

model-releasesarxiv-cs-ro

arXiv:2606.06569v1 Announce Type: new Abstract: Robot manipulation of physical puzzles is important for automatic assembly and disassembly tasks. However, to enable robots to solve physical puzzles, m

Re-Centering Humans in LLM Personalization

arXiv:2606.06614v1 Announce Type: cross Abstract: Despite growing interest, most evaluations of large language models' (LLMs') personalization abilities have relied on synthetic data. It remains uncle

researcharxiv-cs-ai

Re-imagining ISO 26262 in the Age of Autonomous Vehicles: Enhancing Controllability through Transferability and Predictability

arXiv:2606.07437v1 Announce Type: cross Abstract: The ISO 26262 standard defines functional safety for road vehicles through risk assessments based on Severity, Exposure, and Controllability, grounded

safetyarxiv-cs-ai

Semantic-Structural Alignment for Generative Pictorial Charts

arXiv:2606.06498v1 Announce Type: cross Abstract: Traditional statistical graphics are precise but often lack the visual appeal, memorability, and engagement of pictorial charts. We present a generati

safetyarxiv-cs-cv

ADK Arena: Evaluating Agent Development Kits via LLM-as-a-Developer

arXiv:2606.05548v1 Announce Type: cross Abstract: The rapid proliferation of Agent Development Kits (ADKs), SDK-level frameworks for building LLM-powered autonomous agents, has outpaced any empirical

Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation

arXiv:2512.03086v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown remarkable capabilities in code translation, yet their performance deteriorates in low-resource progra

hardwarearxiv-cs-ai

CaMeLs Can Use Computers Too: System-level Security for Computer Use Agents

arXiv:2601.09923v3 Announce Type: replace Abstract: AI agents are vulnerable to prompt injection attacks, where malicious content hijacks agent behavior. Among proposed defenses, architectural isolati

agentsarxiv-cs-ai

CuTeGen: An LLM-Based Agentic Framework for Generation and Optimization of High-Performance GPU Kernels using CuTe

arXiv:2604.01489v2 Announce Type: replace-cross Abstract: High-performance GPU kernels are critical to modern machine learning systems, yet developing them remains a manual, expert-driven process. Rec

hardwarearxiv-cs-ai

Edit-R2: Context-Aware Reinforcement Learning for Multi-Turn Image Editing

arXiv:2606.05950v1 Announce Type: new Abstract: Text-guided image editing has advanced rapidly with diffusion models and unified multimodal foundation models. However, most existing methods remain con

Evaluating Agentic Configuration Repair for Computer Networks

arXiv:2606.06212v1 Announce Type: new Abstract: Misconfigurations in computer networks remain a major source of critical Internet outages. Research is turning to Large Language Models (LLMs) to automa

Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework

arXiv:2606.05710v1 Announce Type: cross Abstract: The increasing penetrations of the critical infrastructure sector in the United States with intelligent digital technologies have greatly increased ex

From Attack Simulation to SIEM Rule: Deterministic Detection-as-Code Synthesis with Probe-Level Traceability

arXiv:2606.05252v1 Announce Type: cross Abstract: Security teams routinely simulate attacks against their own systems to check whether their monitoring would catch a real intruder. These Breach-and-At

GenTI: Benchmarking LLMs for Autonomous IDPS Rule Generation for Unseen Attacks

arXiv:2606.05844v1 Announce Type: cross Abstract: Rule-based Intrusion Detection and Prevention Systems (IDPS) offer precise attack detection as well as mitigation, however their manually crafted, sig

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows

arXiv:2605.12376v2 Announce Type: replace Abstract: Table processing-including cleaning, transformation, augmentation, and matching-is a foundational yet error-prone stage in real-world data pipelines

Synthetic Contrastive Reasoning for Multi-Table Q&A

arXiv:2606.05382v1 Announce Type: new Abstract: Multi-table question answering requires models to retrieve relevant evidence, link schemas, and perform compositional reasoning across relational tables

Will the Agent Recuse Itself? Measuring LLM-Agent Compliance with In-Band Access-Deny Signals

arXiv:2606.06460v1 Announce Type: cross Abstract: As autonomous LLM agents increasingly hold real credentials and operate infrastructure without a human in the loop, operators have no standard way to

Local Ai

AffordanceVLA: A Vision-Language-Action Model Empowering Action Generation through Affordance-Aware Understanding

arXiv:2606.06155v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models leverage the rich world knowledge of pretrained vision-language models (VLMs) to enable instruction-following robo

local-aiarxiv-cs-cv

Almieyar-Oryx-BloomBench: A Bilingual Multimodal Benchmark for Cognitively Informed Evaluation of Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2606.05531v1 Announce Type: cross Abstract: Despite the rapid progress of Vision-Language Models (VLMs), the field lacks benchmarks that rigorously diagnose their true reasoning abilities and ch

BRepCLIP: Contrastive Multimodal Pretraining on BRep Primitives for CAD Understanding

arXiv:2606.05515v1 Announce Type: new Abstract: Learning representations of CAD models is a largely open problem. While 3D representation learning has flourished around point clouds and meshes, the na

researcharxiv-cs-cv

Deep Learning-based 3D Oral Cavity Reconstruction Using 2D Intraoral Images

arXiv:2606.05998v1 Announce Type: new Abstract: Oral 3D modelling is one of the most essential stages in dentistry, and many different approaches, such as impression taking and intraoral scanning, are

researcharxiv-cs-cv

Drishti AI-Event Guardian: An Intelligent Real-Time Crowd Monitoring and Emergency Response System for Mass Gathering Events

arXiv:2606.05185v1 Announce Type: cross Abstract: Mass gathering events are associated with critical safety incidents caused by insufficient crowd monitoring and inadequate emergency response coordina

safetyarxiv-cs-cv

Epistemic Injustice in Language Models: An Audit of Pretraining Filters and Guardrails

arXiv:2606.05936v1 Announce Type: new Abstract: Modern language models rely on pretraining filters to remove undesirable content from training corpora and inference-time guardrails to suppress undesir

safetyarxiv-cs-cl

MotionDisco: Motion Discovery for Extreme Humanoid Loco-Manipulation

arXiv:2606.06139v1 Announce Type: new Abstract: We present MotionDisco, a framework that discovers contact-rich, long-horizon humanoid loco-manipulation motions from scratch, without relying on teleop

applicationsarxiv-cs-ro

VTI-CoT: Visual-Textual Interleaved Chain of Thought for Video Reasoning

model-releasesarxiv-cs-cv

arXiv:2606.05736v1 Announce Type: new Abstract: Video reasoning aims to understand complex temporal events and causal relationships within videos. Recently, Chain-of-Thought (CoT) has been introduced

What's Under the Skin? Estimating Swine Body Condition

arXiv:2606.05611v1 Announce Type: new Abstract: Sow body condition is an important indicator for growers as it has a large impact on lactation performance and piglet survival. However, body condition

applicationsarxiv-cs-cv

3D Temporal Analysis for Autism Spectrum Disorder Screening During Attention Tasks

arXiv:2606.04836v1 Announce Type: new Abstract: Accurate Autism Spectrum Disorder (ASD) screening for school-age children is crucial to identify cases that may have been missed earlier and to enable t

researcharxiv-cs-cv

A New Angle on Bones: Robust Pose Estimation in X-Ray and Ultrasound

model-releasesarxiv-cs-cv

arXiv:2606.04700v1 Announce Type: new Abstract: Measuring the angle between bone structures is a routine task in medical image analysis and provides a key quantitative parameter for diagnosis and trea

ACAT: A Collaborative Platform for Efficient Aspect-Based Sentiment Dataset Annotation

arXiv:2606.04189v1 Announce Type: new Abstract: Aspect-Based Sentiment Analysis (ABSA) requires high-quality datasets to train reliable models. However, existing annotation tools treat output as flat

researcharxiv-cs-cl

AgentJet: A Flexible Swarm Training Framework for Agentic Reinforcement Learning

arXiv:2606.04484v1 Announce Type: new Abstract: We present AgentJet, a distributed swarm training framework for large language model (LLM) agent reinforcement learning. Unlike centralized frameworks t

hardwarearxiv-cs-ai

AlgoVeri: An Aligned Benchmark for Verified Code Generation on Classical Algorithms

arXiv:2602.09464v2 Announce Type: replace-cross Abstract: Vericoding refers to the generation of formally verified code from rigorous specifications. Recent AI models show promise in vericoding, but a

Archi: Agentic Operations at the CMS Experiment

arXiv:2606.04755v1 Announce Type: cross Abstract: We present Archi, an open-source, end-to-end framework for scientific collaborations that combines the systematic ingestion and organization of hetero

agentsarxiv-cs-ai

AUDDT: A Unified Benchmark Toolkit for Audio and Speech Deepfake Detectors

model-releasesarxiv-cs-cl

arXiv:2509.21597v2 Announce Type: replace-cross Abstract: With the prevalence of artificial intelligence (AI)-generated content, such as audio deepfakes, a large body of recent work has focused on dev

Automatic Generation of Titles for Research Papers Using Language Models

arXiv:2606.05085v1 Announce Type: cross Abstract: The title of a research paper conveys its primary idea and, occasionally, its conclusions in a clear and concise manner. Choosing an appropriate title

Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?

arXiv:2506.10912v4 Announce Type: replace Abstract: Toxicity remains a leading cause of early-stage drug development failure. Despite advances in molecular design and property prediction, the task of

ChatSOP: An SOP-Guided MCTS Planning Framework for Controllable LLM Dialogue Agents

arXiv:2407.03884v4 Announce Type: replace-cross Abstract: Dialogue agents powered by Large Language Models (LLMs) show superior performance in various tasks. Despite the better user understanding and

researcharxiv-cs-ai

ClustRecNet: A Novel End-to-End Deep Learning Framework for Clustering Algorithm Recommendation

arXiv:2509.25289v4 Announce Type: replace-cross Abstract: Identifying an effective clustering algorithm for a given dataset remains a fundamental unsupervised learning issue. We introduce ClustRecNet,