Search: “automated”

Simulating Infant First-Person Sensorimotor Experience via Motion Retargeting from Babies to Humanoids

arXiv:2604.27583v1 Announce Type: cross Abstract: Motion retargeting from humans to human-like artificial agents is becoming increasingly important as humanoid robots grow more capable. However, most

researcharxiv-cs-ro

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Research

Static Program Slicing Using Language Models With Dataflow-Aware Pretraining and Constrained Decoding

DGX agent

arXiv:2604.26961v1 Announce Type: cross Abstract: Static program slicing is a fundamental software engineering technique for isolating code relevant to specific variables. While recent learning-based

researcharxiv-cs-ai

1 May 2026

TIO-SHACL: Comprehensive SHACL validation for TMF Intent Ontologies

arXiv:2604.27359v1 Announce Type: new Abstract: Intent-based networking promises to revolutionize telecommunications network management by enabling operators to specify high-level goals rather than lo

researcharxiv-cs-ai

Unsupervised Machine Learning for Osteoporosis Diagnosis Using Singh Index Clustering on Hip Radiographs

arXiv:2411.15253v2 Announce Type: replace-cross Abstract: Osteoporosis, a prevalent condition among the aging population worldwide, is characterized by diminished bone mass and altered bone structure,

researcharxiv-cs-cv

WaferSAGE: Large Language Model-Powered Wafer Defect Analysis via Synthetic Data Generation and Rubric-Guided Reinforcement Learning

arXiv:2604.27629v1 Announce Type: new Abstract: We present WaferSAGE, a framework for wafer defect visual question answering using small vision-language models. To address data scarcity in semiconduct

When Your LLM Reaches End-of-Life: A Framework for Confident Model Migration in Production Systems

arXiv:2604.27082v1 Announce Type: new Abstract: We present a framework for migrating production Large Language Model (LLM) based systems when the underlying model reaches end-of-life or requires repla

applicationsarxiv-cs-ai

World2Minecraft: Occupancy-Driven Simulated Scenes Construction

arXiv:2604.27578v1 Announce Type: new Abstract: Embodied intelligence requires high-fidelity simulation environments to support perception and decision-making, yet existing platforms often suffer from

applicationsarxiv-cs-cv

Hardware

AdaFRUGAL: Adaptive Memory-Efficient Training with Dynamic Control

arXiv:2601.11568v2 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) is highly memory-intensive due to optimizer state overhead. The FRUGAL framework mitigates this with gra

hardwarearxiv-cs-ai

Auto-Relational Reasoning

arXiv:2604.26507v1 Announce Type: new Abstract: Background & Objectives: In the last decade, Machine learning research has grown rapidly, but large models are reaching their soft limits demonstrating

researcharxiv-cs-ai

Benchmarking Complex Multimodal Document Processing Pipelines: A Unified Evaluation Framework for Enterprise AI

arXiv:2604.26382v1 Announce Type: cross Abstract: Most enterprise document AI today is a pipeline. Parse, index, retrieve, generate. Each of those stages has been studied to death on its own -- what's

Benchmarking Deep Learning and Vision Foundation Models for Atypical vs. Normal Mitosis Classification with Cross-Dataset Evaluation

arXiv:2506.21444v4 Announce Type: replace Abstract: Atypical mitosis marks a deviation in the cell division process that has been shown be an independent prognostic marker for tumor malignancy. Howeve

ClassEval-Pro: A Cross-Domain Benchmark for Class-Level Code Generation

arXiv:2604.26923v1 Announce Type: cross Abstract: LLMs have achieved strong results on both function-level code synthesis and repository-level code modification, yet a capability that falls between th

ClawGym: A Scalable Framework for Building Effective Claw Agents

arXiv:2604.26904v1 Announce Type: cross Abstract: Claw-style environments support multi-step workflows over local files, tools, and persistent workspace states. However, scalable development around th

DenseStep2M: A Scalable, Training-Free Pipeline for Dense Instructional Video Annotation

arXiv:2604.26565v1 Announce Type: new Abstract: Long-term video understanding requires interpreting complex temporal events and reasoning over procedural activities. While instructional video corpora,

EmoTransCap: Dataset and Pipeline for Emotion Transition-Aware Speech Captioning in Discourses

arXiv:2604.26417v1 Announce Type: new Abstract: Emotion perception and adaptive expression are fundamental capabilities in human-agent interaction. While recent advances in speech emotion captioning (

agentsarxiv-cs-cl

Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Models

arXiv:2401.00761v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) like ChatGPT are foundational in various applications due to their extensive knowledge from pre-training and fine

applicationsarxiv-cs-ai

Information Extraction from Electricity Invoices with General-Purpose Large Language Models

arXiv:2604.25927v1 Announce Type: new Abstract: Information extraction from semi-structured business documents remains a critical challenge for enterprise management. This study evaluates the capabili

Learning to Ask: When LLM Agents Meet Unclear Instruction

arXiv:2409.00557v4 Announce Type: replace-cross Abstract: Equipped with the capability to call functions, modern large language models (LLMs) can leverage external tools for addressing a range of task

OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction

arXiv:2604.25602v2 Announce Type: replace Abstract: Deploying production-ready multi-agent systems (MAS) in complex industrial environments remains challenging due to limitations in scalability, obser

agentsarxiv-cs-ai

Risk Reporting for Developers' Internal AI Model Use

arXiv:2604.24966v1 Announce Type: cross Abstract: Frontier AI companies first deploy their most advanced models internally, for weeks or months of safety testing, evaluation, and iteration, before a p

safetyarxiv-cs-ai

SAGE: A Strategy-Aware Graph-Enhanced Generation Framework For Online Counseling

arXiv:2604.26630v1 Announce Type: new Abstract: Effective mental health counseling is a complex, theory-driven process requiring the simultaneous integration of psychological frameworks, real-time dis

safetyarxiv-cs-cl

Seamless Indoor-Outdoor Mapping for INGENIOUS First Responders

arXiv:2604.26368v1 Announce Type: new Abstract: In several applications it is desired to have 3D models not only from the outdoor spaces but also from inside the building. In the context of First Resp

researcharxiv-cs-cv

Training Computer Use Agents to Assess the Usability of Graphical User Interfaces

arXiv:2604.26020v1 Announce Type: cross Abstract: Usability testing with experts and potential users can assess the effectiveness, efficiency, and user satisfaction of graphical user interfaces (GUIs)

agentsarxiv-cs-ai

Value-Guided Iterative Refinement and the DIQ-H Benchmark for Evaluating VLM Robustness

arXiv:2512.03992v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are essential for embodied AI and safety-critical applications, such as robotics and autonomous systems. However

BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling

arXiv:2604.24999v1 Announce Type: new Abstract: Thoracic Computed Tomography (CT) scans offer detailed insights into the intricate branching network of the airway tree, which is essential for understa

BLASST: Dynamic BLocked Attention Sparsity via Softmax Thresholding

arXiv:2512.12087v3 Announce Type: replace Abstract: The growing demand for long-context inference capabilities in Large Language Models (LLMs) has intensified the computational and memory bottlenecks

Exploring Remote Photoplethysmography for Neonatal Pain Detection from Facial Videos

arXiv:2604.25680v1 Announce Type: new Abstract: Unaddressed pain in neonates can lead to adverse effects, including delayed development and slower weight gain, emphasising the need for more objective

Faithfulness-QA: A Counterfactual Entity Substitution Dataset for Training Context-Faithful RAG Models

arXiv:2604.25313v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) models frequently produce answers grounded in parametric memory rather than the retrieved context, undermining the

GAIA-v2-LILT: Multilingual Adaptation of Agent Benchmark beyond Translation

arXiv:2604.24929v1 Announce Type: new Abstract: Agent benchmarks remain largely English-centric, while their multilingual versions are often built with machine translation (MT) and limited post-editin

GPT-Image-2 in the Wild: A Twitter Dataset of Self-Reported AI-Generated Images from the First Week of Deployment

arXiv:2604.25370v1 Announce Type: new Abstract: The release of GPT-image-2 by OpenAI marks a watershed moment in AI-generated imagery: the boundary between photographic reality and synthetic content h

GS-Playground: A High-Throughput Photorealistic Simulator for Vision-Informed Robot Learning

arXiv:2604.25459v1 Announce Type: new Abstract: Embodied AI research is undergoing a shift toward vision-centric perceptual paradigms. While massively parallel simulators have catalyzed breakthroughs

researcharxiv-cs-ro

Heterogeneous Variational Inference for Markov Degradation Hazard Models: Discretized Mixture with Interpretable Clusters

arXiv:2604.24818v1 Announce Type: new Abstract: Bayesian finite mixture models can identify discrete risk clusters (low-risk vs. high-risk equipment), but face three critical bottlenecks: (1) insuffic

applicationsarxiv-cs-lg

Measuring the Sensitivity of Classification Models with the Error Sensitivity Profile

arXiv:2604.25765v1 Announce Type: new Abstract: The quality of training data is critical to the performance of machine learning models. In this paper, the Error Sensitivity Profile (ESP) is proposed.

researcharxiv-cs-lg

Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health

arXiv:2410.09635v2 Announce Type: replace Abstract: Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, acc

researcharxiv-cs-lg

Local Ai

A Digital Pathology Resource for Liver Cancer Quantification with Datasets, Benchmarks, and Tools

arXiv:2604.22858v1 Announce Type: new Abstract: Liver cancer, especially hepatocellular carcinoma (HCC), imposes a substantial global disease burden. Accurate diagnosis and prognostic assessment direc

local-aiarxiv-cs-cv

A Multi-Dimensional Audit of Politically Aligned Large Language Models

arXiv:2604.24429v1 Announce Type: new Abstract: As the application of Large Language Models (LLMs) spreads across various industries, there are increasing concerns about the potential for their misuse

safetyarxiv-cs-cl

Accelerating New Product Introduction for Visual Quality Inspection via Few-Shot Diffusion-Based Defect Synthesis

arXiv:2604.22850v1 Announce Type: new Abstract: Industrial visual inspection systems often suffer from a severe scarcity of labeled defect data, particularly during the early stages of New Product Int

researcharxiv-cs-cv

AgentEval: DAG-Structured Step-Level Evaluation for Agentic Workflows with Error Propagation Tracking

arXiv:2604.23581v1 Announce Type: cross Abstract: Agentic systems that chain reasoning, tool use, and synthesis into multi-step workflows are entering production, yet prevailing evaluation practices l

agentsarxiv-cs-cl

Agentic Witnessing: Pragmatic and Scalable TEE-Enabled Privacy-Preserving Auditing

arXiv:2604.24203v1 Announce Type: cross Abstract: Auditing the semantic properties of proprietary data creates a fundamental tension: verification requires transparent access, while proprietary rights

Algorithmic Administration and the EU AI Act: Legal Principles for Public Sector Use of AI

arXiv:2604.22765v1 Announce Type: cross Abstract: The increasing use of artificial intelligence (AI) by public authorities introduces both opportunities for innovation and significant challenges for t

safetyarxiv-cs-ai

An Empirical Evaluation of Locally Deployed LLMs for Bug Detection in Python Code

arXiv:2604.23361v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong performance on a wide range of software engineering tasks, including code generation and analysi

AnemiaVision: Non-Invasive Anemia Detection via Smartphone Imagery Using EfficientNet-B3 with TrivialAugmentWide, Mixup Augmentation, and Persistent Patient History Management

arXiv:2604.22964v1 Announce Type: new Abstract: Anemia affects over one billion people globally and remains severely under-diagnosed in low-resource regions where laboratory blood tests are inaccessib

safetyarxiv-cs-cv

Case-Specific Rubrics for Clinical AI Evaluation: Methodology, Validation, and LLM-Clinician Agreement Across 823 Encounters

arXiv:2604.24710v1 Announce Type: new Abstract: Objective. Clinical AI documentation systems require evaluation methodologies that are clinically valid, economically viable, and sensitive to iterative

agentsarxiv-cs-ai

Cataract-LMM Large-Scale Multi-Source Multi-Task Benchmark for Deep Learning in Surgical Video Analysis

arXiv:2510.16371v2 Announce Type: replace-cross Abstract: The development of computer-assisted surgery systems relies on large-scale, annotated datasets. Existing cataract surgery resources lack the d

CiteAudit: You Cited It, But Did You Read It? A Benchmark for Verifying Scientific References in the LLM Era

arXiv:2602.23452v2 Announce Type: replace Abstract: Scientific research relies on accurate citation for attribution and integrity, yet large language models (LLMs) introduce a new risk: fabricated ref

Credal Concept Bottleneck Models for Epistemic-Aleatoric Uncertainty Decomposition

arXiv:2604.24170v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) predict through human-interpretable concepts, but they typically output point concept probabilities that conflate epist

researcharxiv-cs-ai

CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks

arXiv:2510.17687v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) achieve strong reasoning and perception capabilities but are increasingly vulnerable to jailbreak att

CyberCane: Neuro-Symbolic RAG for Privacy-Preserving Phishing Detection with Formal Ontology Reasoning

arXiv:2604.23563v1 Announce Type: cross Abstract: Privacy-critical domains require phishing detection systems that satisfy contradictory constraints: near-zero false positives to prevent workflow disr

applicationsarxiv-cs-ai