Search: “automated”

Architecting Agentic Communities using Design Patterns

arXiv:2601.03624v3 Announce Type: replace Abstract: The rapid evolution of Large Language Models (LLM) and subsequent Agentic AI technologies requires systematic architectural guidance for building so

Auditing medical multi-agent AI reveals risks of false consensus

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DGX agent

arXiv:2510.10185v2 Announce Type: replace-cross Abstract: Large language models are increasingly being assembled into medical multi-agent systems that emulate multidisciplinary consultation through sp

safetyarxiv-cs-ai

26 May 2026

Beyond Control-Flow: Integrating the Resource Perspective into Multi-Collaborative Process Modeling from Text

arXiv:2605.24546v1 Announce Type: new Abstract: Process modeling is a sub-domain of Business Process Management (BPM) focused on the translation of process artifacts into formal models. This task trad

researcharxiv-cs-ai

Beyond Final Answers: Auditing Trajectory-Level Hallucinations in Multi-Agent Industrial Workflows

arXiv:2605.24219v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents that reason, use tools, and act over multiple steps. Yet most hallucination

BODHI: Precise OS Kernel Specification Inference

arXiv:2605.23931v1 Announce Type: new Abstract: The formal verification of operating system kernels requires precise specifications that capture the intended behavior of system calls. Writing these sp

Claw-Anything: Benchmarking Always-On Personal Assistants with Broader Access to User's Digital World

arXiv:2605.26086v1 Announce Type: new Abstract: Large language model agents are increasingly envisioned as always-on personal assistants with access to anything relevant in the user's digital world. Y

CRISP -- Clustering-Based Redundancy-Reduced Instance Sampling for Pathology Case Representation and Retrieval

arXiv:2605.24253v1 Announce Type: cross Abstract: Digital pathology archives increasingly contain multiple whole-slide images (WSIs) per case, capturing spatially distinct tumour regions and reflectin

DRInQ: Evaluating Conversational Implicature with Controlled Context Variation

arXiv:2605.24267v1 Announce Type: new Abstract: Human conversation relies heavily on conversational implicature, in which speakers convey meanings that are suggested rather than explicitly stated. Alt

Dynamic Optimization and Safety Indicator Injection for Jailbreaking Text-to-Image Models with Multimodal Safety Filters

arXiv:2505.18979v2 Announce Type: replace Abstract: Text-to-image (T2I) models can generate not-safe-for-work (NSFW) content, motivating multi-stage safety pipelines with both text and image filters.

Empirical Analysis and Detection of Hallucinations in LLM-Generated Bug Report Summaries

arXiv:2605.24137v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to generate summaries of software bug reports, including sections such as Steps-to-Reproduce (S2R),

EPPC-OASIS: Ontology-Aware Adaptation and Structured Inference Refinement for Electronic Patient-Provider Communication Mining in Secure Messages

arXiv:2605.24172v1 Announce Type: new Abstract: Secure patient-provider messages contain clinically important communication behaviors that are difficult to characterize manually at scale. The Electron

FairJudge: Abstention-Aware Multimodal Judges for Fairness and Alignment Evaluation in Text-to-Image Models

arXiv:2510.22827v3 Announce Type: replace-cross Abstract: Evaluating text-to-image (T2I) systems requires judging not only whether an image matches a prompt, but also whether socially salient attribut

Faithfulness Metrics Don't Measure Faithfulness: A Meta-Evaluation with Ground Truth

arXiv:2605.25052v1 Announce Type: new Abstract: Chains of thought (CoTs) have become central in interpreting and auditing behaviors of large language models. Yet growing evidence suggests that these t

GeoSVG-RL: Geometry-Aware Reinforcement Learning for Layout-Constrained Text-to-SVG Diagram Generation

arXiv:2605.25447v1 Announce Type: new Abstract: Generating structured, editable diagrams remains a significant challenge for contemporary large language models, despite their proficiency in general-pu

safetyarxiv-cs-cl

GlobalDentBench: A Multinational Benchmark for Evaluating LLM Clinical Reasoning in Dentistry with Expert Calibration

arXiv:2605.24636v1 Announce Type: new Abstract: While large language models (LLMs) hold transformative potential for medicine, their reasoning robustness and safety in real-world clinical scenarios re

How Much Do Large Language Model Cheat on Evaluation? Benchmarking Overestimation under the One-Time-Pad-Based Framework

arXiv:2507.19219v2 Announce Type: replace Abstract: Overestimation in evaluating large language models (LLMs) has become an increasing concern. Due to the contamination of public benchmarks or imbalan

Inverting the Shield: Systematically Generating Safety Tests from Policy Specifications

arXiv:2605.24883v1 Announce Type: new Abstract: The widespread integration of Large Language Models (LLMs) necessitates rigorous and systematic safety evaluation. Existing paradigms either rely on con

Iterate Until Retrieved: Factual Nugget Optimization for Discoverable Continual Corrections in Agentic RAG

arXiv:2605.25641v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) systems in complex B2B (business-to-business) settings may often receive free-form response feedback. Rathe

agentsarxiv-cs-cl

IVR-R1: Refining Trajectories through Iterative Visual-Grounded Reasoning in Reinforcement Learning

arXiv:2605.23997v1 Announce Type: cross Abstract: Multimodal large language models via reinforcement learning (RL) have demonstrated remarkable capabilities in complex visual reasoning tasks, yet they

Applications

Lake Detection and Water Quality Estimation in Sentinel-2 Data

arXiv:2605.24515v1 Announce Type: new Abstract: With climate change and increasing human pressure on natural landscapes, inland water resources are becoming progressively scarcer, more vulnerable, and

applicationsarxiv-cs-lg

Tutorials

Leveraging Spreading Activation for Improved Document Retrieval in Knowledge-Graph-Based RAG Systems

arXiv:2512.15922v3 Announce Type: replace Abstract: Despite initial successes and a variety of architectures, retrieval-augmented generation systems still struggle to reliably retrieve and connect the

tutorialsarxiv-cs-ai

Memory-Induced Tool-Drift in LLM Agents

model-releasesarxiv-cs-lg

arXiv:2605.24941v1 Announce Type: cross Abstract: Modern LLM agents combine long-term memory for personalization with tool-calling interfaces for taking actions in the world -- a combination underpinn

Meta-Engineering Harnesses for AI-Native Software Production: A Contract-Driven Adversarial Verification Architecture with Early Deployment Report

arXiv:2605.25665v1 Announce Type: cross Abstract: AI-native software development is often evaluated at the level of individual models, prompts, or generated artifacts. This framing is insufficient for

Methodology for Creating a Clinically Verified Dermoscopic Image Dataset

arXiv:2605.25168v1 Announce Type: cross Abstract: This study presents a methodology for constructing a clinically verified dataset of dermatoscopic images for medical informatics research. The relevan

researcharxiv-cs-ai

MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence

arXiv:2505.23764v3 Announce Type: replace-cross Abstract: Spatial intelligence is essential for multimodal large language models (MLLMs) operating in the complex physical world. Existing benchmarks, h

Multi-Agent Coordination Adaptation via Structure-Guided Orchestration

arXiv:2605.25746v1 Announce Type: cross Abstract: As large language model (LLM)-based multi-agent systems scale to handle increasingly complex tasks, balancing structural stability and dynamic adaptab

PrivFusion: A Privacy-preserving Multi-Agent Framework for Harmonizing Distributed Datasets

arXiv:2605.24249v1 Announce Type: new Abstract: The growing availability of clinical data has increased the use of machine learning, yet centralized data aggregation is often infeasible for sensitive

ProActor: Timing-Aware Reinforcement Learning for Proactive Task Scheduling Agents

arXiv:2605.24900v1 Announce Type: new Abstract: Proactive task-oriented agents must autonomously anticipate user needs, identify actionable opportunities, and trigger software actions at appropriate m

Tutorials

QASA: Quality-Aware Semantic Augmentation for Robust Multimodal Sentiment Analysis

arXiv:2601.06870v2 Announce Type: replace-cross Abstract: Multimodal large language models have demonstrated strong ability in capturing semantic representations for multimodal sentiment analysis. The

tutorialsarxiv-cs-ai

Local Ai

Retrieval-Augmented Detection of Potentially Abusive Clauses in Chilean Terms of Service

arXiv:2605.26019v1 Announce Type: cross Abstract: Online Terms of Service often function as contracts of adhesion, creating asymmetries that may expose consumers to potentially abusive clauses. In Chi

local-aiarxiv-cs-ai

StructBreak: Structural Cognitive Overload-Induced Safety Failures in MLLMs

arXiv:2605.25534v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) excel at structural reasoning yet suffer from a sharp logical brittleness in structural consistency. We term th

The Model Is Not the Product: A Dual-Pillar Architecture for Local-First Psychological Coaching

arXiv:2605.24411v1 Announce Type: new Abstract: Existing language model applications struggle to meet the demand for emotionally oriented support, primarily due to their inability to maintain deep, pe

The Perception-Physics Paradox: Probing Scientific Alignment with TC-Bench

model-releasesarxiv-cs-lg

arXiv:2605.24782v1 Announce Type: new Abstract: While Vision Foundation Models (VFMs) excel at predictive tasks on satellite imagery, their performance can arise from visual correlations rather than u

TopoAlign: Topology-Aware Visual Representation Alignment

arXiv:2605.25541v1 Announce Type: cross Abstract: Neural networks encode inputs as high-dimensional vectors, known as representations, that capture how models process data by encoding task-relevant st

When Gradients Collide: Failure Modes of Multi-Objective Prompt Optimization for LLM Judges

arXiv:2605.26046v1 Announce Type: cross Abstract: Customizing an LLM judge to a specific task or domain often involves optimizing its prompt across multiple evaluation criteria simultaneously. Textual

researcharxiv-cs-ai

Advanced AI Service Provisioning in O-RAN through LLM Engine Integration

arXiv:2605.23809v1 Announce Type: cross Abstract: The Open Radio Access Network (O-RAN) architecture allows AI to be embedded directly into the RAN through modular xApps and rApps, yet creating these

researcharxiv-cs-lg

Can AI Guess What You Know? Performance Comparison of Large Language Models for Human Domain Knowledge Estimation From Communication Logs

arXiv:2605.22971v1 Announce Type: new Abstract: Employees often struggle to identify ``who knows what,'' leading to organizational productivity losses. We investigate whether Large Language Models (LL

ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models

arXiv:2605.23694v1 Announce Type: new Abstract: Chart descriptions are essential for accessibility, cross-modal retrieval, and assisting readers in extracting insights from complex visualizations. As

Controlled Personalization in Legacy Media Online Services: A Case Study in News Recommendation

arXiv:2510.09136v2 Announce Type: replace-cross Abstract: Personalized news recommendations have become a standard feature of large news aggregation services, optimizing user engagement through automa

EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization

arXiv:2605.23412v1 Announce Type: new Abstract: While social media platforms, such as Twitter, provide a medium for large-scale opinion sharing during news events, it is manually impossible for indivi

safetyarxiv-cs-cl

EvalVerse: Pipeline-Aware and Expert-Calibrated Benchmarking for Professional Cinematic Video Generation

arXiv:2605.23271v1 Announce Type: cross Abstract: The rapid evolution of generative video foundation models has propelled the field toward professional-grade cinematic synthesis. To achieve such deman

Local Ai

From Activation to Causality: Discovery of Causal Visual Representations in the Human Brain

arXiv:2605.23895v1 Announce Type: new Abstract: Identifying which brain regions represent a visual concept in the human brain is a central challenge in neuroscience. Existing approaches have localized

local-aiarxiv-cs-cv

Tutorials

GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals

arXiv:2504.09846v2 Announce Type: replace-cross Abstract: Frequent and long-term exposure to hyperglycemia increases the risk of chronic complications, including neuropathy, nephropathy, and cardiovas

tutorialsarxiv-cs-ai

ImProver 2: Iteratively Self-Improving LMs for Neurosymbolic Proof Optimization

arXiv:2605.22885v1 Announce Type: new Abstract: Formal mathematics libraries are rapidly expanding, creating a growing need to refactor verified proofs for maintainability and to improve training data

Investigating Robot Control Policy Learning for Autonomous X-ray-guided Spine Procedures

arXiv:2511.03882v2 Announce Type: replace-cross Abstract: Imitation learning-based robot control policies are enjoying renewed interest in video-based robotics. However, it remains unclear whether thi

LLM-driven design of physics-constrained constitutive models: two agents are better than one

model-releasesarxiv-cs-lg

arXiv:2605.23754v1 Announce Type: new Abstract: Developing constitutive models that capture how materials deform under load traditionally requires years of specialized expertise in continuum mechanics

Machine learning applied to emerald gemstone grading: framework proposal and creation of a public dataset

arXiv:2605.23777v1 Announce Type: new Abstract: The grading of gemstones is currently a manual procedure performed by gemologists. A popular approach uses reference stones, where those are visually in

researcharxiv-cs-cv

MaMa: A Game-Theoretic Approach for Designing Safe Agentic Systems

arXiv:2602.04431v2 Announce Type: replace Abstract: LLM-based multi-agent systems have demonstrated impressive capabilities, but they also introduce significant safety risks when individual agents fai