Search: “models”

M3Net: A Macro-to-Meso-to-Micro Clinical-inspired Hierarchical 3D Network for Pulmonary Nodule Classification

arXiv:2605.12570v1 Announce Type: new Abstract: The accurate classification of benign and malignant pulmonary nodules in CT scans is critical for early lung cancer screening, yet remains challenging d

researcharxiv-cs-cv

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Machine Learning-Driven Multimodal Spectroscopic Liquid Biopsy for Early Multicancer Detection

DGX agent

arXiv:2605.13218v1 Announce Type: new Abstract: Cancer is one of the leading causes of death worldwide, making the development of rapid, minimally invasive, label-free and scalable diagnostic strategi

researcharxiv-cs-lg

14 May 2026

MAP: A Map-then-Act Paradigm for Long-Horizon Interactive Agent Reasoning

arXiv:2605.13037v1 Announce Type: new Abstract: Current interactive LLM agents rely on goal-conditioned stepwise planning, where environmental understanding is acquired reactively during execution rat

MMSkills: Towards Multimodal Skills for General Visual Agents

arXiv:2605.13527v1 Announce Type: new Abstract: Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as te

MUJICA: Multi-skill Unified Joint Integration of Control Architecture for Wheeled-Legged Robots

arXiv:2605.13058v1 Announce Type: new Abstract: Wheeled-legged robots hold promise for traversing complex terrains and offer superior mobility compared to legged robots. However, wheeled-legged robots

safetyarxiv-cs-ro

Object Manipulation of the Variable Topology Truss system

arXiv:2605.13086v1 Announce Type: new Abstract: This paper presents an object manipulation strategy for the Variable Topology Truss (VTT) system, a truss robot that comprises actuated truss members co

researcharxiv-cs-ro

Offline Two-Player Zero-Sum Markov Games with KL Regularization

arXiv:2605.13025v1 Announce Type: new Abstract: We study the problem of learning Nash equilibria in offline two-player zero-sum Markov games. While existing approaches often rely on explicit pessimism

On Privacy-Preserving Image Transmission in Low-Altitude Networks: A Swin Transformer-Based Framework with Federated Learning

arXiv:2605.12566v1 Announce Type: cross Abstract: The rapid development of low-altitude economy has driven the proliferation of Unmanned Aerial Vehicle (UAV) applications, including logistics, inspect

On the Sample Complexity of Differentially Private Policy Optimization

arXiv:2510.21060v3 Announce Type: replace-cross Abstract: Policy optimization (PO) is a cornerstone of modern reinforcement learning (RL), with diverse applications spanning robotics, healthcare, and

PG-LRF: Physiology-Guided Latent Rectified Flow for Electro-Hemodynamic PPG-to-ECG Generation

arXiv:2605.12541v1 Announce Type: cross Abstract: Electrocardiography (ECG) is the clinical standard for cardiac assessment but requires dedicated hardware that does not scale to daily-life monitoring

Phy-CoSF: Physics-Guided Continuous Spectral Fields Reconstruction and Super-Resolution for Snapshot Compressive Imaging

arXiv:2605.13583v1 Announce Type: new Abstract: Recent advances have demonstrated that coded aperture snapshot spectral imaging (CASSI) systems show great potential for capturing 3D hyperspectral imag

researcharxiv-cs-cv

Position: Assistive Agents Need Accessibility Alignment

arXiv:2605.13579v1 Announce Type: new Abstract: Assistive agents for Blind and Visually Impaired (BVI) users require accessibility alignment as a first-class design objective. Despite rapid progress i

Posterior Bayesian Neural Networks with Dependent Weights

arXiv:2507.22095v5 Announce Type: replace-cross Abstract: We consider fully connected and feedforward deep neural networks with dependent and possibly heavy-tailed weights, as introduced in [26], to a

Potential and challenges of generative adversarial networks for super-resolution in 4D Flow MRI

arXiv:2508.14950v2 Announce Type: replace-cross Abstract: 4D Flow Magnetic Resonance Imaging (4D Flow MRI) enables non-invasive quantification of blood flow and hemodynamic parameters. However, its cl

Prime Successor Irreducibility: Turing Machine Complexity, Kolmogorov Complexity, and Weakness-Based Formulations

arXiv:2605.12504v1 Announce Type: cross Abstract: We develop conjectures and theorems expressing the idea that the prime sequence exhibits computational irreducibility in the transition from one prime

Tutorials

Probabilistic Prediction Markets with Intermittent Contributions

arXiv:2510.13385v3 Announce Type: replace Abstract: Although both data availability and the demand for accurate forecasts are increasing, collaboration between stakeholders is often constrained by dat

tutorialsarxiv-cs-lg

Protocol-Driven Development: Governing Generated Software Through Invariants and Evidence

arXiv:2605.12981v1 Announce Type: cross Abstract: Automated program synthesis has reduced the cost of producing candidate implementations, but it introduces a harder governance problem: determining wh

Pyramid Self-contrastive Learning Framework for Test-time Ultrasound Image Denoising

arXiv:2605.12567v1 Announce Type: cross Abstract: The inherent electronic and speckle noise complicates clinical interpretation of ultrasound images. Conventional denoising methods rely on explicit no

QuickLAP: Quick Language-Action Preference Learning for Semi-Autonomous Systems

arXiv:2511.17855v2 Announce Type: replace Abstract: Robots must learn from both what people do and what they say, but either modality alone is often incomplete: physical corrections are grounded but a

RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Records

arXiv:2507.15867v2 Announce Type: replace-cross Abstract: Rare diseases affect 1 in 10 Americans yet remain systematically underdocumented in clinical records. ICD-based systems cannot capture their b

Re-evaluating Minimum Bayes Risk Decoding for Automatic Speech Recognition

arXiv:2510.19471v2 Announce Type: replace-cross Abstract: Recent work has shown that sample-based Minimum Bayes Risk (MBR) decoding outperforms beam search in text-to-text generation tasks, such as ma

Real-World Challenges in Fake News Detection: Dealing with Posts by Cold Users

arXiv:2605.12511v1 Announce Type: cross Abstract: Social media serves as a primary source of information in the current digital era. Many people consume a vast range of information in a very short spa

applicationsarxiv-cs-lg

Relative Pose-Velocity Estimation Using Dual IMU Measurements and Relative Position Sensing

arXiv:2605.13031v1 Announce Type: cross Abstract: This paper addresses the problem of estimating the relative pose (position and orientation) and velocity of a vehicle with respect to a moving target,

researcharxiv-cs-ro

RMNP: Row-Momentum Normalized Preconditioning for Scalable Matrix-Based Optimization

arXiv:2603.20527v3 Announce Type: replace Abstract: Preconditioned adaptive methods have gained significant attention for training deep neural networks, as they capture rich curvature information of t

Robust and Explainable Bicuspid Aortic Valve Diagnosis Using Stacked Ensembles on Echocardiography

arXiv:2605.13730v1 Announce Type: cross Abstract: Transthoracic echocardiography (TTE) is the first-line imaging modality for diagnosing bicuspid aortic valve (BAV), yet diagnostic performance varies

Robust and Safe Multi-Agent Reinforcement Learning with Communication for Autonomous Vehicles: From Simulation to Hardware

arXiv:2506.00982v3 Announce Type: replace Abstract: Deep multi-agent reinforcement learning (MARL) has been demonstrated effectively in simulations for multi-robot problems. For autonomous vehicles, t

safetyarxiv-cs-ro

Selective Off-Policy Reference Tuning with Plan Guidance

arXiv:2605.11505v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards helps reasoning, but GRPO-style methods stall on hard prompts where all sampled rollouts fail. SORT a

Semantic knowledge guides innovation and drives cultural evolution

arXiv:2510.12837v3 Announce Type: replace-cross Abstract: Cultural evolution allows ideas and technologies to accumulate across generations, reaching their most complex and open-ended form in humans.

SP-GCRL: Influence Maximization on Incomplete Social Graphs

arXiv:2605.12513v1 Announce Type: cross Abstract: Influence maximization (IM) in real platforms is challenged by incomplete, noisy social graphs and non-stationary diffusion dynamics. We propose SP-GC

Spectral Flattening Is All Muon Needs: How Orthogonalization Controls Learning Rate and Convergence

arXiv:2605.13079v1 Announce Type: cross Abstract: Muon orthogonalizes the momentum buffer before each update, replacing its singular values with ones via Newton-Schulz iterations. This simple change l

Stable Attention Response for Reliable Precipitation Nowcasting

arXiv:2605.13181v1 Announce Type: cross Abstract: Precipitation nowcasting remains challenging due to the highly localized, rapidly evolving, and heterogeneous nature of atmospheric dynamics. Although

Still Camouflage, Moving Illusion: View-Induced Trajectory Manipulation in Autonomous Driving

arXiv:2605.12743v1 Announce Type: cross Abstract: Existing physical adversarial attacks on vision-based autonomous driving induce time-evolving perception errors, including biased object tracking or t

agentsarxiv-cs-cv

STORM: Segment, Track, and Object Re-Localization from a Single Image

arXiv:2511.09771v3 Announce Type: replace Abstract: Accurate 6D pose estimation and tracking are core capabilities for physical AI systems, yet real-world deployment remains brittle and labor-intensiv

applicationsarxiv-cs-cv

Strikingness-Aware Evaluation for Temporal Knowledge Graph Reasoning

arXiv:2605.13153v1 Announce Type: new Abstract: Temporal Knowledge Graph Reasoning (TKGR) aims at inferring missing (especially future) events from historical data. Current evaluation in TKGR uniforml

Supervised Deep Multimodal Matrix Factorization for Interpretable Brain Network Analysis

arXiv:2605.13312v1 Announce Type: new Abstract: We present Supervised Deep Multimodal Matrix Factorization (SD3MF), an interpretable framework for integrative brain network analysis that generalizes S

SymbolSight: Minimizing Inter-Symbol Interference for Reading with Prosthetic Vision

arXiv:2601.17326v2 Announce Type: replace Abstract: Retinal prostheses restore limited visual perception, but low spatial resolution and temporal persistence make reading difficult. In sequential lett

researcharxiv-cs-cv

T-TExTS (Teaching Text Expansion for Teacher Scaffolding): Enhancing Text Selection in High School Literature through Knowledge Graph-Based Recommendation

arXiv:2506.12075v2 Announce Type: replace-cross Abstract: High school English Literature teachers often encounter barriers to assembling diverse, thematically aligned text sets due to limited planning

Test-time Sparsity for Extreme Fast Action Diffusion

arXiv:2605.13316v1 Announce Type: new Abstract: Action diffusion excels at high-fidelity action generation but incurs heavy computational costs owing to its iterative denoising nature. Despite current

safetyarxiv-cs-cv

The Joint Gromov Wasserstein Objective for Multiple Object Matching

arXiv:2511.16868v2 Announce Type: replace Abstract: The Gromov-Wasserstein (GW) distance serves as a powerful tool for matching objects in metric spaces. However, its traditional formulation is constr

applicationsarxiv-cs-cv

The Payment Heterogeneity Index: An Integrated Unsupervised Framework for High-Volume Procurement Oversight and Decision Support

arXiv:2605.12547v1 Announce Type: cross Abstract: Public procurement is vulnerable to error, fraud and corruption, yet high transaction volumes overwhelm oversight. While research often focuses on ten

TinySDP: Real Time Semidefinite Optimization for Certifiable and Agile Edge Robotics

arXiv:2605.13748v1 Announce Type: new Abstract: Semidefinite programming (SDP) provides a principled framework for convex relaxations of nonconvex geometric constraints in motion planning, yet existin

researcharxiv-cs-ro

Towards Robust Federated Multimodal Graph Learning under Modality Heterogeneity

arXiv:2605.12584v1 Announce Type: cross Abstract: Recently, multimodal graph learning (MGL) has garnered significant attention for integrating diverse modality information and structured context to su

applicationsarxiv-cs-ai

Trajectory-Level Data Augmentation for Offline Reinforcement Learning

arXiv:2605.13401v1 Announce Type: new Abstract: We propose a data augmentation method for offline reinforcement learning, motivated by active positioning problems. Particularly, our approach enables t

safetyarxiv-cs-lg

VideoSEAL: Mitigating Evidence Misalignment in Agentic Long Video Understanding by Decoupling Answer Authority

arXiv:2605.12571v1 Announce Type: cross Abstract: Long video question answering requires locating sparse, time-scattered visual evidence within highly redundant content. Although current MLLMs perform

What Do You Think I Think? Accounting for Human Beliefs Using Second-Order Theory of Mind

arXiv:2605.12745v1 Announce Type: cross Abstract: Discrepancies between an agent's actual knowledge and what a person thinks the agent knows can hinder interactions. If an agent could detect such disc

What Information Matters? Graph Out-of-Distribution Detection via Tri-Component Information Decomposition

arXiv:2605.13032v1 Announce Type: new Abstract: Graph neural networks are widely used for node classification, but they remain vulnerable to out-of-distribution (OOD) shifts in node features and graph

What Limits Vision-and-Language Navigation ?

arXiv:2605.13328v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) is a cornerstone of embodied intelligence. However, current agents often suffer from significant performance degr

When Should an AI Workflow Release? Always-Valid Inference for Black-Box Generate-Verify Systems

arXiv:2605.12947v1 Announce Type: cross Abstract: LLM-enabled AI workflows increasingly produce outputs through iterative generate-evaluate-revise loops. Each iteration can improve the candidate, but