Search: “models”

Inferring Sensitive Attributes from Knowledge Graph Embeddings: Attack and Defense Strategies

arXiv:2605.19644v1 Announce Type: cross Abstract: Knowledge Graphs (KGs) are a powerful representation of linked data, offering flexibility, semantic richness, and support for knowledge enrichment and

applicationsarxiv-cs-lg

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Safety

k-Inductive Neural Barrier Certificates for Unknown Nonlinear Dynamics

DGX agent

arXiv:2605.20108v1 Announce Type: cross Abstract: While conventional (k=1) discrete-time barrier certificate conditions impose strict safety constraints by requiring the function to be non-increasing

safetyarxiv-cs-ai

20 May 2026

Agents

KadiAssistant: A conversational AI Agent for information retrieval in Kadi4Mat

arXiv:2605.18850v1 Announce Type: cross Abstract: We introduce KadiAssistant, a privacy-by-design AI assistant integrated into the Kadi research data ecosystem, enabling researchers to efficiently acc

agentsarxiv-cs-ai

LaCoVL-FER: Landmark-Guided Contrastive Learning Network with Vision-Language Enhancement for Facial Expression Recognition

arXiv:2605.19821v1 Announce Type: new Abstract: Facial Expression Recognition (FER) in the wild is still challenging due to uncontrolled variations in pose, occlusion, and illumination. Most existing

applicationsarxiv-cs-cv

Language Mutations Sustain the Persistences of Conspiracy Theories on Social Media

arXiv:2605.20050v1 Announce Type: new Abstract: This study investigates how language mutations affect the persistent diffusion of conspiracy theories on social media. Drawing on a three-year dataset o

researcharxiv-cs-cl

Learned Static Function Data Structures

arXiv:2510.27588v3 Announce Type: replace-cross Abstract: We consider the task of constructing a data structure for associating a static set of keys with values, while allowing arbitrary output values

Learning Orthonormal Bases for Function Spaces

arXiv:2605.19959v1 Announce Type: new Abstract: Infinite-dimensional orthonormal basis expansions play a central role in representing and computing with function spaces due to their favorable linear a

Learning with Foresight: Enhancing Neural Routing Policy via Multi-Node Lookahead Prediction

arXiv:2605.19975v1 Announce Type: cross Abstract: Neural policies have shown promise in solving vehicle routing problems due to their reduced reliance on handcrafted heuristics. However, current train

LionMuon: Alternating Spectral and Sign Descent for Efficient Training

arXiv:2605.19811v1 Announce Type: new Abstract: In large-scale optimization, the cheapness and effectiveness of update steps are the most crucial factors for a successful optimizer. Sign-based optimiz

LP-Eval: Rubric and Dataset for Measuring the Quality of Legal Proposition Generation

arXiv:2605.19815v1 Announce Type: cross Abstract: Legal proposition generation is central to legal reasoning and doctrinal scholarship, yet remain under-examined in Legal NLP. This paper investigates

applicationsarxiv-cs-ai

Mapping Uncharted Symmetries: Machine Discovery in Combinatorics

arXiv:2605.19063v1 Announce Type: new Abstract: Inspired by long-standing open problems in algebraic combinatorics, we show that modern machine learning can meaningfully contribute to verifiable mathe

Mechanistic Interpretability Needs Philosophy

arXiv:2506.18852v2 Announce Type: replace-cross Abstract: Mechanistic interpretability (MI) aims to explain how neural networks work by uncovering their underlying mechanisms. As the field grows in in

researcharxiv-cs-ai

Minimalist Visual Inertial Odometry

arXiv:2605.19990v1 Announce Type: cross Abstract: Visual-Inertial Odometry(VIO), which is critical to mobile robot navigation, uses cameras with a large number of pixels. Capturing and processing came

applicationsarxiv-cs-cv

Navigating the Emotion Tree: Hierarchical Hyperbolic RAG for Multimodal Emotion Recognition

arXiv:2605.18884v1 Announce Type: cross Abstract: Multimodal emotion recognition aims to integrate text, audio, and video sources to understand human affective states. Although multimodal large langua

Neural Configuration-Space Barriers for Manipulation Planning and Control

arXiv:2503.04929v3 Announce Type: replace-cross Abstract: Planning and control for high-dimensional robot manipulators in cluttered dynamic environments require computational efficiency and robust saf

safetyarxiv-cs-lg

Local Ai

NORi: An ML-Augmented Ocean Boundary Layer Parameterization

arXiv:2512.04452v2 Announce Type: replace-cross Abstract: NORi is a machine learning (ML) parameterization of ocean boundary layer turbulence that is physics-based and augmented with neural networks.

local-aiarxiv-cs-ai

Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR

arXiv:2605.20164v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has made post-training highly effective when correctness can be checked automatically. However, many impo

Tutorials

OP2GS: Object-Aware 3D Gaussian Splatting with Dual-Opacity Primitives

arXiv:2605.20044v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) provides an explicit and efficient scene representation, but its primitives lack inherent object-level identity, hindering

tutorialsarxiv-cs-cv

OpenComputer: Verifiable Software Worlds for Computer-Use Agents

arXiv:2605.19769v1 Announce Type: new Abstract: We present OpenComputer, a verifier-grounded framework for constructing verifiable software worlds for computer-use agents. OpenComputer integrates four

researcharxiv-cs-ai

Agents

Operationalising Artificial Intelligence Bills of Materials (AIBOMs) for Verifiable AI Provenance and Lifecycle Assurance

arXiv:2605.19755v1 Announce Type: cross Abstract: Artificial Intelligence (AI) systems are increasingly dependent on complex, multi-layered software supply chains that introduce challenges for reprodu

agentsarxiv-cs-ai

Physics-informed simulation framework for realistic sonar image generation and statistical validation

arXiv:2605.19712v1 Announce Type: new Abstract: Synthetic sonar datasets offer a scalable alternative to costly real-world acquisition, yet their utility remains limited by the absence of rigorous qua

safetyarxiv-cs-cv

Agents

PragLocker: Protecting Agent Intellectual Property in Untrusted Deployments via Non-Portable Prompts

arXiv:2605.05974v2 Announce Type: replace-cross Abstract: LLM agents rely on prompts to implement task-specific capabilities based on foundation LLMs, making agent prompts valuable intellectual proper

agentsarxiv-cs-ai

Probabilistic Recursively Feasible Motion Planning Under Uncertain Environments

arXiv:2605.19015v1 Announce Type: cross Abstract: Safe motion planning in uncertain, time-varying environments is challenging because the safe region can change unpredictably across planning steps, of

safetyarxiv-cs-ro

Prognostic Value of Lung Ultrasound Biomarkers for Readmission Risk in Congestive Heart Failure: A Pilot Data-Driven Analysis

arXiv:2605.18878v1 Announce Type: cross Abstract: Hospital readmission within 30 days of discharge is a leading driver of morbidity, mortality, and avoidable healthcare expenditure in congestive heart

applicationsarxiv-cs-cv

Qayyem: A Real-time Platform for Scoring Proficiency of Arabic Essays

arXiv:2603.01009v2 Announce Type: replace Abstract: Over the past years, Automated Essay Scoring (AES) systems have gained increasing attention as scalable and consistent solutions for assessing the p

researcharxiv-cs-cl

Quantum Autoencoder for Multivariate Time Series Anomaly Detection

arXiv:2504.17548v2 Announce Type: replace-cross Abstract: Anomaly Detection (AD) defines the task of identifying observations or events that deviate from typical - or normal - patterns, a critical cap

applicationsarxiv-cs-lg

Rapid patient-specific neural networks for intraoperative X-ray to volume registration

arXiv:2503.16309v2 Announce Type: replace-cross Abstract: Advanced navigation techniques in image-guided interventions and surgical robotics require the rapid and precise alignment of 3D preoperative

safetyarxiv-cs-cv

Retrieval-Augmented Linguistic Calibration

arXiv:2605.19344v1 Announce Type: new Abstract: Linguistic cues such as 'I believe' and 'probably' offer an intuitive interface for communicating confidence, yet a generalisable, principled calibratio

researcharxiv-cs-cl

Return of Frustratingly Easy Unsupervised Video Domain Adaptation

arXiv:2605.19510v1 Announce Type: new Abstract: Unsupervised video domain adaptation (UVDA) is a practical but under-explored problem. In this paper, we propose a frustratingly easy UVDA method, calle

Robust Mitigation of Age-Dependent Confounding Effects via Sample-Difficulty Decorrelation

arXiv:2605.19230v1 Announce Type: new Abstract: Age dependent performance disparities in medical image classification often arise because age acts as a confounder, linking imaging morphology with dise

RoHIL: Robust Human-in-the-Loop Robotic Reinforcement Learning Against Illumination Variations

arXiv:2605.19924v1 Announce Type: new Abstract: Human-in-the-loop reinforcement learning systems achieve near-perfect success on the workstation where they are trained, but collapse when the same robo

safetyarxiv-cs-ro

RoomPilot: Controllable Indoor Scene Synthesis via Multimodal Semantic Parsing

arXiv:2512.11234v2 Announce Type: replace Abstract: Generating controllable indoor scenes is fundamental to applications in game development, architectural visualization, and embodied AI. However, exi

Sampling-Based Safe Reinforcement Learning

arXiv:2605.19469v1 Announce Type: cross Abstract: Safe exploration remains a fundamental challenge in reinforcement learning (RL), limiting the deployment of RL agents in the real world. We propose Sa

Set-Valued Policy Learning

arXiv:2605.19830v1 Announce Type: new Abstract: Conventional treatment policies map patient covariates to a single recommended intervention in order to maximize expected clinical outcomes. Although a

safetyarxiv-cs-lg

SetCon: Towards Open-Ended Referring Segmentation via Set-Level Concept Prediction

arXiv:2605.20110v1 Announce Type: new Abstract: Referring segmentation grounds natural-language queries to pixel-level masks, but extending it to complex scenarios with multiple instances, cross-categ

SETUP: Sentence-level English-To-Uniform Meaning Representation Parser

arXiv:2512.07068v3 Announce Type: replace Abstract: Uniform Meaning Representation (UMR) is a novel graph-based semantic representation which captures the core meaning of a text, with flexibility inco

applicationsarxiv-cs-cl

SimGym: A Framework for A/B Test Simulation in E-Commerce with Traffic-Grounded VLM Agents

arXiv:2605.19219v1 Announce Type: new Abstract: A/B testing remains the gold standard for evaluating modifications to e-commerce storefronts, yet it diverts traffic, requires weeks to reach statistica

Hardware

Soft Learning

arXiv:2605.18889v1 Announce Type: cross Abstract: Modern machine learning forces practitioners to choose between powerful but expensive deep networks and fast but limited classical algorithms. Here we

hardwarearxiv-cs-ai

Spatially Prompted Visual Trajectory Prediction for Egocentric Manipulation

arXiv:2605.20085v1 Announce Type: new Abstract: Robotic manipulation is often specified through language instructions or task identifiers, yet cluttered environments with similar objects are better ha

safetyarxiv-cs-cv

StruMPL: Multi-task Dense Regression under Disjoint Partial Supervision and MNAR Labels

arXiv:2605.19931v1 Announce Type: cross Abstract: Estimating forest aboveground biomass (AGB) from Earth observation combines two structurally incompatible label sources: spaceborne lidar provides can

Symmetry in the Wild: The Role of Equivariance in Neural Fluid Surrogates

arXiv:2605.18816v1 Announce Type: cross Abstract: Neural surrogates enable orders-of-magnitude acceleration of computational fluid dynamics (CFD) simulations, with the potential to transform engineeri

TERGAD: Structure-Aware Text-Enhanced Representations for Graph Anomaly Detection

arXiv:2605.19738v1 Announce Type: cross Abstract: Graph Anomaly Detection (GAD) aims to identify atypical graph entities, such as nodes, edges, or substructures, that deviate significantly from the ma

applicationsarxiv-cs-ai

The impact of observation density on Bayesian inversion of latent dynamics in shock-dominated flows

arXiv:2605.19076v1 Announce Type: new Abstract: Inferring unknown initial states in shock-dominated compressible flows from sparse and noisy measurements is a challenging ill-posed inverse problem due

Local Ai

Thinking in Scales: Accelerating Gigapixel Pathology Image Analysis via Adaptive Continuous Reasoning

arXiv:2605.19491v1 Announce Type: new Abstract: Traditional whole slide image (WSI) analysis methods typically rely on the multiple instance learning (MIL) paradigm, which extracts patch-level feature

local-aiarxiv-cs-cv

TIDE: Asymmetric Neural Circuits for Stabilized Temporal Inhibitory-Excitatory Dynamics

arXiv:2605.19403v1 Announce Type: new Abstract: Recent Continuous Thought Machine architecture decouples internal computation from external inputs via neural dynamics, but relies on multi-layer percep

Unsupervised Unfolded rPCA (U2-rPCA): Deep Interpretable Clutter Filtering for Ultrasound Microvascular Imaging

arXiv:2510.00660v2 Announce Type: replace Abstract: High-sensitivity clutter filtering is a fundamental step in ultrasound microvascular imaging. Singular value decomposition (SVD) and robust principa

Warm-starting active-set solvers using graph neural networks

arXiv:2511.13174v2 Announce Type: replace Abstract: Quadratic programming (QP) solvers are widely used in real-time control and optimization, but their computational cost often limits applicability in

When the Majority Votes Wrong, the Intervention Timing for Test-Time Reinforcement Learning Hides in the Extinction Window

arXiv:2605.19444v1 Announce Type: cross Abstract: Test-time reinforcement learning (TTRL) reports substantial accuracy gains on mathematical reasoning benchmarks using majority vote as a pseudo-label

researcharxiv-cs-ai