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Why Expert Alignment Is Hard: Evidence from Subjective Evaluation

arXiv:2605.04972v1 Announce Type: new Abstract: Aligning large language models with expert judgment is especially difficult in subjective evaluation tasks, where experts may disagree, rely on tacit cr

safetyarxiv-cs-cl

7 May 2026

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Why Geometric Continuity Emerges in Deep Neural Networks: Residual Connections and Rotational Symmetry Breaking

DGX agent

arXiv:2605.04971v1 Announce Type: cross Abstract: Weight matrices in deep networks exhibit geometric continuity -- principal singular vectors of adjacent layers point in similar directions. While this

researcharxiv-cs-cl

7 May 2026

YOTOnet: Zero-Shot Cross-Domain Fault Diagnosis via Domain-Conditioned Mixture of Experts

arXiv:2605.04528v1 Announce Type: new Abstract: Mechanical equipment forms the critical backbone of modern industrial production, yet domain shift severely limits the generalization of deep learning b

applicationsarxiv-cs-lg

7 May 2026

12 Angry AI Agents: Evaluating Multi-Agent LLM Decision-Making Through Cinematic Jury Deliberation

arXiv:2605.01986v1 Announce Type: new Abstract: What if the twelve jurors of Sidney Lumet's 12 Angry Men (1957) were not men, but large language models? Would the one juror who disagrees still be able

3D Human Face Reconstruction with 3DMM face model from RGB image

arXiv:2605.03996v1 Announce Type: new Abstract: Nowadays as convolution neural networks demonstrate its powerful problem-solving ability in the area of image processing, efforts have been made to reco

4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere

arXiv:2602.10094v2 Announce Type: replace Abstract: We present 4RC, a unified feed-forward framework for 4D reconstruction from monocular videos. Unlike existing approaches that typically decouple mot

6G Needs Agents: Toward Agentic AI-Native Networks for Autonomous Intelligence

arXiv:2605.01546v1 Announce Type: cross Abstract: Sixth-generation (6G) networks are increasingly envisioned as AI-native infrastructures integrating communication, sensing, and computing into a unifi

A Benchmark for Interactive World Models with a Unified Action Generation Framework

model-releasesarxiv-cs-cv

arXiv:2605.03941v1 Announce Type: new Abstract: Achieving Artificial General Intelligence (AGI) requires agents that learn and interact adaptively, with interactive world models providing scalable env

Local Ai

A Cellular Doctrine of Morality: Intrinsic Active Precision and the Mind-Reality Overload Dilemma

arXiv:2605.01376v1 Announce Type: new Abstract: Current AI systems, grounded in oversimplified neuroscience, risk eroding the distinction between truth and falsehood. They maximize reward by amplifyin

local-aiarxiv-cs-ai

A Certifably Correct Algorithm for Generalized Robot-World and Hand-Eye Calibration

arXiv:2507.23045v2 Announce Type: replace Abstract: Automatic extrinsic sensor calibration is a fundamental problem for multi-sensor platforms. Reliable and general-purpose solutions should be computa

researcharxiv-cs-ro

A Closed-Form Adaptive-Landmark Kernel for Certified Point-Cloud and Graph Classification

arXiv:2605.04046v1 Announce Type: new Abstract: We introduce PALACE (Persistence Adaptive-Landmark Analytic Classification Engine), the data-adaptive companion to PLACE, paying a small cross-validatio

A-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion

arXiv:2605.03360v1 Announce Type: cross Abstract: We present A-CODE, a fully atomic unified one-stage protein co-design model that simultaneously refines discrete atom types and continuous atom coordi

A Comparison of Traditional Machine Learning Algorithms and LSTM-Based Deep Learning Models for Email Sentiment Analysis

arXiv:2605.03440v1 Announce Type: new Abstract: The rapid growth of electronic communication has necessitated more robust systems for email classification and sentiment detection. This study presents

researcharxiv-cs-cl

Agents

A Compound AI Agent for Conversational Grant Discovery

arXiv:2605.02366v1 Announce Type: new Abstract: Research funding discovery remains fundamentally fragmented: researchers navigate disparate agency portals (e.g., in the United States, NSF, NIH, DARPA,

agentsarxiv-cs-ai

A Comprehensive Analysis of Tokenization and Self-Supervised Learning in End-to-End Automatic Speech Recognition applied on French Language

arXiv:2605.03696v1 Announce Type: new Abstract: The performance of end-to-end automatic speech recognition (ASR) systems enables their increasing integration into numerous applications. While there ar

researcharxiv-cs-cl

A Deeper Dive into the Irreversibility of PolyProtect: Making Protected Face Templates Harder to Invert

model-releasesarxiv-cs-cv

arXiv:2605.03857v1 Announce Type: new Abstract: This work presents a deeper analysis of the 'irreversibility' property of PolyProtect, a biometric template protection method initially proposed for sec

A Domain Incremental Continual Learning Benchmark for ICU Time Series Model Transportability

model-releasesarxiv-cs-lg

arXiv:2605.03832v1 Announce Type: new Abstract: In recent years, machine learning has made significant progress in clinical outcome prediction, demonstrating increasingly accurate results. However, th

Local Ai

A Few-Step Generative Model on Cumulative Flow Maps

arXiv:2605.03623v1 Announce Type: new Abstract: We propose a unified, few-step generative modeling framework based on cumulative flow maps for long-range transport in probability space, inspired by fl

local-aiarxiv-cs-lg

A Framework for Exploring and Disentangling Intersectional Bias: A Case Study in Fetal Ultrasound

model-releasesarxiv-cs-cv

arXiv:2605.02942v1 Announce Type: cross Abstract: Bias in medical AI is often framed as a problem of representation. However, in image-based tasks such as fetal ultrasound, performance disparities can

A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning

arXiv:2605.03499v1 Announce Type: new Abstract: We study expected generalization bounds for the Hierarchical Federated Learning (HFL) setup using Wasserstein distance. We introduce a generalized frame

A Knowledge-Driven LLM-Based Decision-Support System for Explainable Defect Analysis and Mitigation Guidance in Laser Powder Bed Fusion

arXiv:2605.01100v1 Announce Type: new Abstract: This work presents a knowledge-driven decision-support system that integrates structured defect knowledge with LLM-based reasoning to provide explainabl

safetyarxiv-cs-ai

Agents

A Low-Latency Fraud Detection Layer for Detecting Adversarial Interaction Patterns in LLM-Powered Agents

arXiv:2605.01143v1 Announce Type: new Abstract: Large Language Model (LLM)-powered agents demonstrate strong capabilities in autonomous task execution, tool use, and multi-step reasoning. However, the

agentsarxiv-cs-ai

A Neuro-Symbolic Framework for Accountability in Public-Sector AI

arXiv:2512.12109v3 Announce Type: replace-cross Abstract: Automated eligibility systems increasingly determine access to essential public benefits, but the explanations they generate often fail to ref

applicationsarxiv-cs-ai

A note on the unique properties of the Kullback--Leibler divergence for sampling via gradient flows

arXiv:2507.04330v2 Announce Type: replace-cross Abstract: We consider the problem of sampling from a probability distribution pi which admits a density w.r.t. a dominating measure. It is well known th

A Paradigm for Interpreting Metrics and Identifying Critical Errors in Automatic Speech Recognition

arXiv:2605.03671v1 Announce Type: new Abstract: The most commonly used metrics for evaluating automatic speech transcriptions, namely Word Error Rate (WER) and Character Error Rate (CER), have been he

researcharxiv-cs-cl

A Partition-Based Generating Function for Row-Convex Polyominoes

arXiv:2605.03203v1 Announce Type: cross Abstract: An alternative generating function is proposed to enumerate row-convex polyominoes without internal holes on a discrete grid. The approach is based on

A Perfectly Truthful Calibration Measure

arXiv:2508.13100v3 Announce Type: replace Abstract: Calibration requires that predictions are conditionally unbiased and, therefore, reliably interpretable as probabilities. A calibration measure quan

A Robust Unsupervised Domain Adaptation Framework for Medical Image Classification Using RKHS-MMD

arXiv:2605.03787v1 Announce Type: new Abstract: Labeling medical images is a major bottleneck in the field of medical imaging, as it requires domain-specific expertise, and it gets further complicated

safetyarxiv-cs-cv

A Scoping Review of Deep Learning Methods for Photoplethysmography Data

arXiv:2401.12783v3 Announce Type: replace-cross Abstract: Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad

applicationsarxiv-cs-lg

A Sentence Relation-Based Approach to Sanitizing Malicious Instructions

arXiv:2605.01078v1 Announce Type: cross Abstract: Retrieval-augmented generation and tool-integrated LLM agents increasingly depend on external textual sources. This reliance broadens the available at

researcharxiv-cs-ai

Agents

A Study of Belief Revision Postulates in Multi-Agent Systems (Extended Version)

arXiv:2605.02249v1 Announce Type: new Abstract: We investigate the belief revision problem in epistemic planning, i.e., what will be the beliefs of all agents in a multi-agent system after an agent ga

agentsarxiv-cs-ai

A Target-Free Harmonization Method for MRI

arXiv:2605.01282v1 Announce Type: cross Abstract: In MRI, variations in scan parameters, sequence, or hardware can lead to discrepancies in image appearance, even for the same subject. These inconsist

researcharxiv-cs-ai

A Three-Stage Offline SDRE-Based Control Framework for Human Motion Reproduction on a Suspended Bipedal Robot

arXiv:2506.04680v2 Announce Type: replace Abstract: During the development of wearable exoskeletons, evaluations involving human subjects pose inherent safety risks. Therefore, systematic testing is o

safetyarxiv-cs-ro

A Unified Framework for Tabular Generative Modeling: Loss Functions, Benchmarks, and Improved Multi-objective Bayesian Optimization Approaches

arXiv:2405.16971v2 Announce Type: replace Abstract: Deep learning (DL) models require extensive data to achieve strong performance and generalization. Deep generative models (DGMs) offer a solution by

applicationsarxiv-cs-lg

A Universal Reproducing Kernel Hilbert Space from Polynomial Alignment and IMQ Distance

arXiv:2605.03262v1 Announce Type: new Abstract: We introduce the Yat kernel $k_{b,arepsilon}(mathbf{w},mathbf{x})=frac{(mathbf{w}^opmathbf{x}+b)^2}{|mathbf{x}-mathbf{w}|^2+arepsilon},qquad bge 0, arep

safetyarxiv-cs-lg

A User-Centric Analysis of Explainability in AI-Based Medical Image Diagnosis

arXiv:2605.02903v1 Announce Type: cross Abstract: In recent years, AI systems in the medical domain have advanced significantly. However, despite outperforming humans, they are rarely used in practice

A Vision-Based Shared-Control Teleoperation Scheme for Controlling the Robotic Arm of a Four-Legged Robot

arXiv:2508.14994v3 Announce Type: replace-cross Abstract: In hazardous and remote environments, robotic systems perform critical tasks demanding improved safety and efficiency. Among these, quadruped

safetyarxiv-cs-cv

ABD: Default Exception Abduction in Finite First Order Worlds

arXiv:2602.18843v3 Announce Type: replace Abstract: We introduce ABD, a benchmark for default-exception abduction over finite first-order worlds. Given a background theory with an abnormality predicat

Tutorials

ABox Abduction for Inconsistent Knowledge Bases under Repair Semantics

arXiv:2605.01341v1 Announce Type: cross Abstract: Given a knowledge base (KB) with a non-entailed fact, the ABox abduction problem asks for possible extensions of the KB that would entail this fact. T

tutorialsarxiv-cs-ai

AcademiClaw: When Students Set Challenges for AI Agents

arXiv:2605.02661v1 Announce Type: new Abstract: Benchmarks within the OpenClaw ecosystem have thus far evaluated exclusively assistant-level tasks, leaving the academic-level capabilities of OpenClaw

Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding

arXiv:2505.24791v2 Announce Type: replace Abstract: Discrete normalizing flows are promising generative models with advantages such as analytical log-likelihood computation and end-to-end training. Ho

Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models

arXiv:2605.00968v1 Announce Type: cross Abstract: Positional encoding plays a pivotal role in determin?ing the extrapolation and generalization performance of wireless foundation models for channel st

safetyarxiv-cs-ai

Adaptive Data Compression and Reconstruction for Memory-Bounded EEG Continual Learning

arXiv:2605.03085v1 Announce Type: new Abstract: Electroencephalography (EEG) signals provide millisecond-level temporal resolution but their analysis is limited by remarkable noise and inter-subject v

Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity

arXiv:2605.03393v1 Announce Type: cross Abstract: Contextual MDPs are powerful tools with wide applicability in areas from biostatistics to machine learning. However, specializing them to offline data

Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning

arXiv:2605.03495v1 Announce Type: new Abstract: We develop graph-based methods for semi-supervised learning based on label propagation on a data similarity graph. When data is abundant or arrive in a

Adaptive Negative Scheduling for Graph Contrastive Learning

model-releasesarxiv-cs-lg

arXiv:2605.03076v1 Announce Type: new Abstract: Graph contrastive learning (GCL) has become a central paradigm for self-supervised representation learning in computational intelligence, with applicati

ADAPTS: Agentic Decomposition for Automated Protocol-agnostic Tracking of Symptoms

arXiv:2605.03212v1 Announce Type: cross Abstract: Modeling latent clinical constructs from unconstrained clinical interactions is a unique challenge in affective computing. We present ADAPTS (Agentic

safetyarxiv-cs-cl

AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages

model-releasesarxiv-cs-cl

arXiv:2601.06395v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly multilingual, yet open models continue to underperform relative to proprietary systems, with the gap m