Search: “papers”

Cross-Polarization Fusion of VV AND VH SAR Observations for Improved Flood Mapping

arXiv:2605.02153v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) imagery is widely used for flood monitoring due to its all-weather and day-night imaging capability. However, flood mappi

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Research

CSGuard: Toward Forgery-Resistant Watermarking in Diffusion Models via Compressed Sensing Constraint

DGX agent

arXiv:2605.01479v1 Announce Type: new Abstract: Latent-based diffusion model watermarking embeds watermarks into generated images' latent space to enable content attribution, offering a training-free

researcharxiv-cs-cv

5 May 2026

CUE: Concept-Aware Multi-Label Expansion to Mitigate Concept Confusion in Long-Tailed Learning

arXiv:2605.01309v1 Announce Type: new Abstract: Long-tailed distributions are common in real-world recognition tasks, where a few head classes have many samples while most tail classes have very few.

safetyarxiv-cs-cv

DBLP: Phase-Aware Bounded-Loss Transport for Burst-Resilient Distributed ML Training

arXiv:2605.01989v1 Announce Type: new Abstract: Distributed machine learning (ML) training has become a necessity with the prevalence of billion to trillion-parameter-scale models. While prior work ha

Decoding-Time Debiasing via Process Reward Models: From Controlled Fill-in to Open-Ended Generation

arXiv:2605.02348v1 Announce Type: new Abstract: Large language models pick up social biases from the data they are trained on and carry those biases into downstream applications, often reinforcing ste

Tutorials

Decouple and Cache: KV Cache Construction for Streaming Video Understanding

arXiv:2605.01858v1 Announce Type: new Abstract: Streaming video understanding requires processing unbounded video streams with limited memory and computation, posing two key challenges. First, continu

tutorialsarxiv-cs-cv

Deep Learning for Multi-Antenna Modulation Recognition of Radio Signals

arXiv:2605.00849v1 Announce Type: cross Abstract: Multi-antenna receiving systems have become a prevalent technical solution in communication systems. Meanwhile, deep learning has achieved significant

Deep Time Series Models: A Comprehensive Survey and Benchmark

arXiv:2407.13278v3 Announce Type: replace Abstract: Time series, characterized by a sequence of data points organized in a discrete-time order, are ubiquitous in real-world scenarios. Unlike other dat

Demographic-Aware Transfer Learning for Sleep Stage Classification in Clinical Polysomnography

arXiv:2605.02245v1 Announce Type: new Abstract: Automated sleep stage classification typically employs a single population-agnostic model, disregarding established demographic variations in sleep arch

Dino-NestedUNet: Unlocking Foundation Vision Encoders for Pathology Tumor Bulk Segmentation via Dense Decoding

arXiv:2605.00894v1 Announce Type: new Abstract: Vision foundation models (VFMs), such as DINOv3, provide rich semantic representations that are promising for computational pathology. However, many cur

Applications

Does it Really Count? Assessing Semantic Grounding in Text-Guided Class-Agnostic Counting

arXiv:2605.02752v1 Announce Type: new Abstract: Open-world text-guided class-agnostic counting (CAC) has emerged as a flexible paradigm for counting arbitrary object classes by using natural language

applicationsarxiv-cs-cv

DuFal: Dual-Frequency-Aware Learning for High-Fidelity Extremely Sparse-view CBCT Reconstruction

arXiv:2601.15416v2 Announce Type: replace Abstract: Sparse-view Cone-Beam Computed Tomography reconstruction from limited X-ray projections remains a challenging problem in medical imaging due to the

Edge Case Detection in Automated Driving: Methods, Challenges and Future Directions

arXiv:2410.08491v2 Announce Type: replace Abstract: Automated vehicles promise to enhance transportation safety and efficiency. However, ensuring their reliability in real-world conditions remains cha

safetyarxiv-cs-ro

EmoMM: Benchmarking and Steering MLLM for Multimodal Emotion Recognition under Conflict and Missingness

arXiv:2605.01024v1 Announce Type: new Abstract: Multimodal Emotion Recognition (MER) is critical for interpreting real-world interactions. While Multimodal Large Language Models (MLLM) have shown prom

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning

arXiv:2605.02073v1 Announce Type: new Abstract: Mathematical reasoning is a key benchmark for large language models. Reinforcement learning is a standard post-training mechanism for improving the reas

Agents

Equation-Free Digital Twins for Nonlinear Structural Dynamics

arXiv:2605.00950v1 Announce Type: cross Abstract: Monitoring high-dimensional engineering structures in extreme environments is limited by non-stationary excitation, nonlinear structural kinematics, a

agentsarxiv-cs-lg

Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks

arXiv:2605.01484v1 Announce Type: new Abstract: With the rapidly improving reasoning abilities of Large Language Models (LLMs), there is also a rising demand to use them in a wide variety of domains.

Evaluating Tabular Representation Learning for Network Intrusion Detection

arXiv:2605.02519v1 Announce Type: new Abstract: Classic Network Intrusion Detection Systems (NIDS) often rely on manual feature engineering to extract meaningful patterns from network traffic data. Ho

Evidence-Based Landing Site Selection and Vison-Based Landing for UAVs in Unstructured Environments

arXiv:2605.01432v1 Announce Type: new Abstract: Autonomous landing in cluttered or unstructured environments remains a safety-critical challenge for unmanned aerial vehicles (UAVs), particularly under

safetyarxiv-cs-ro

Evolving Token Communication with Parametric Memory Network

arXiv:2605.01869v1 Announce Type: cross Abstract: Token communication has emerged as a promising framework for efficient wireless transmission by representing source data as compact semantic tokens. H

Exact Higher-Order Derivatives for SE(3) via Analytical/AD Methods

model-releasesarxiv-cs-ro

arXiv:2605.02252v1 Announce Type: new Abstract: Fast prototyping of new SE(3) estimation objectives remains awkward in practice. Modern Lie-group frameworks -- GTSAM, manif, Sophus, SymForce, Ceres --

Feature Weighting Improves Pool-Based Sequential Active Learning for Regression

arXiv:2604.02019v2 Announce Type: replace Abstract: Pool-based sequential active learning for regression (ALR) optimally selects a small number of samples sequentially from a large pool of unlabeled s

Applications

Federated Semi-Supervised Graph Neural Networks with Prototype-Guided Pseudo-Labeling for Privacy-Preserving Gestational Diabetes Mellitus Prediction

arXiv:2605.01810v1 Announce Type: new Abstract: Gestational Diabetes Mellitus (GDM) is a high-prevalence pregnancy complication that requires accurate early risk stratification to reduce maternal and

applicationsarxiv-cs-lg

Feedback-Normalized Developer Memory for Reinforcement-Learning Coding Agents: A Safety-Gated MCP Architecture

arXiv:2605.01567v1 Announce Type: cross Abstract: Large language model (LLM) coding agents increasingly operate over repositories, terminals, tests, and execution traces across long software-engineeri

FeedbackLLM: Metadata driven Multi-Agentic Language Agnostic Test Case Generator with Evolving prompt and Coverage Feedback

arXiv:2605.01264v1 Announce Type: cross Abstract: Traditional approaches to test case generation often involve manual effort and incur significant computational overhead. Additionally, these approache

Fin-PRM: A Domain-Specialized Process Reward Model for Financial Reasoning in Large Language Models

arXiv:2508.15202v2 Announce Type: replace Abstract: Process Reward Models (PRMs) supervise intermediate reasoning steps in large language models (LLMs), but existing PRMs are mainly trained on general

Fine-Tuning Impairs the Balancedness of Foundation Models in Long-tailed Personalized Federated Learning

arXiv:2605.02247v1 Announce Type: new Abstract: Personalized federated learning (PFL) with foundation models has emerged as a promising paradigm enabling clients to adapt to heterogeneous data distrib

Finite-Sample Analysis of Elimination in Active Hypothesis Testing

arXiv:2605.01039v1 Announce Type: new Abstract: A fixed-confidence, finite-sample problem of active hypothesis testing arises in many safety-critical applications. Situated in the context of sequentia

Agents

Flux4D: Flow-based Unsupervised 4D Reconstruction

arXiv:2512.03210v2 Announce Type: replace Abstract: Reconstructing large-scale dynamic scenes from visual observations is a fundamental challenge in computer vision, with critical implications for rob

agentsarxiv-cs-cv

Tutorials

Forager: a lightweight testbed for continual learning with partial observability in RL

arXiv:2605.01131v1 Announce Type: new Abstract: In continual reinforcement learning (CRL), good performance requires never-ending learning, acting, and exploration in a big, partially observable world

tutorialsarxiv-cs-lg

Local Ai

FractalMamba++: Scaling Vision Mamba Across Resolutions via Hilbert Fractal Geometr

arXiv:2505.14062v3 Announce Type: replace Abstract: Vision Mamba offers linear complexity for long visual sequences, yet its performance depends critically on how a two-dimensional patch grid is seria

local-aiarxiv-cs-cv

From Concept to Capability: Evaluating 3D Gaussian Splatting for Synthetic Scene Editing in Autonomous Driving

arXiv:2605.01995v1 Announce Type: new Abstract: The perception of an Autonomous Driving System (ADS) critically depends on relevant, comprehensive, and diverse datasets to ensure its safety while oper

safetyarxiv-cs-cv

Gen-Searcher: Reinforcing Agentic Search for Image Generation

arXiv:2603.28767v2 Announce Type: replace Abstract: Recent image generation models have shown strong capabilities in generating high-fidelity and photorealistic images. However, they are fundamentally

Generalized Distributional Alignment Games for Unbiased Answer-Level Fine-Tuning

arXiv:2605.02435v1 Announce Type: new Abstract: The Distributional Alignment Game framework provides a powerful variational perspective on Answer-Level Fine-Tuning (ALFT). However, standard algorithms

safetyarxiv-cs-lg

Gradient-Discrepancy Acquisition for Pool-Based Active Learning

arXiv:2605.02609v1 Announce Type: new Abstract: The effectiveness of active learning hinges on the choice of the acquisition criterion by which a learning algorithm selects potentially informative dat

Green Energy Management for Sustainable Data Centers Using Deep Reinforcement Learning

arXiv:2507.21153v2 Announce Type: replace Abstract: The exponential growth of digital services has positioned data centers among the most energy-intensive infrastructures in the modern economy, raisin

safetyarxiv-cs-lg

Growing Transformers: Modular Composition and Layer-wise Expansion on a Frozen Substrate

arXiv:2507.07129v3 Announce Type: replace-cross Abstract: We study a constrained training regime for decoder-only Transformers in which the token interface is fixed, previously trained dense blocks ar

Heavy-Tailed Principal Component Analysis

arXiv:2603.11308v2 Announce Type: replace Abstract: Principal Component Analysis (PCA) is a cornerstone of dimensionality reduction, yet its classical formulation relies critically on second-order mom

High-Speed, Scalable Sensor Readout for Dexterous Robotic Hands via Shift-Register Multiplexing

arXiv:2605.01434v1 Announce Type: new Abstract: Dexterous robotic hands require high-speed multimodal sensing across many degrees of freedom, yet existing readout architectures often impose trade-offs

researcharxiv-cs-ro

Hybrid Quantum Reinforcement Learning with QAOA for Improved Vehicle Routing Optimization

arXiv:2605.01574v1 Announce Type: new Abstract: Vehicle Routing Problem (VRP) is one of the most complex NP-hard combinatorial optimization problem in transportation and logistics that requires a dyna

safetyarxiv-cs-lg

Improving Imbalanced Multi-Label Chest X-Ray Diagnosis via CBAM-Enhanced CNN Backbones

arXiv:2605.02328v1 Announce Type: new Abstract: Chest radiography is a widely used imaging modality for thoracic disease diagnosis, yet its conventional interpretation remains time-consuming and heavi

InfiltrNet: Dual-Branch CNN-Transformer Architecture for Brain Tumor Infiltration Risk Prediction

arXiv:2605.02230v1 Announce Type: new Abstract: Gliomas are aggressive brain tumors that infiltrate surrounding tissue beyond the visible tumor margins observed on Magnetic Resonance Imaging (MRI). Pr

Instance-Aware Parameter Configuration in Bilevel Late Acceptance Hill Climbing for the Electric Capacitated Vehicle Routing Problem

model-releasesarxiv-cs-ai

arXiv:2605.00572v1 Announce Type: new Abstract: Algorithm performance in combinatorial optimization is highly sensitive to parameter settings, while a single globally tuned configuration often fails t

Investigating Anthropometric Fidelity in SAM 3D Body

arXiv:2601.06035v2 Announce Type: replace-cross Abstract: The release of SAM 3D Body is a recent development in human mesh recovery, demonstrating improved performance in producing clean, topologicall

safetyarxiv-cs-cv

Joint Architecture-Token-Bitwidth Multi-Axis Optimization of Vision Transformers for Semiconductor IC Packaging

arXiv:2605.01742v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved strong performance in visual recognition, yet their deployment in resource-constrained industrial environments

Know Yourself Better: Diverse Object-Related Features Improve Open Set Recognition

arXiv:2404.10370v3 Announce Type: replace Abstract: Open set recognition (OSR) is a critical aspect of machine learning, addressing the challenge of detecting novel classes during inference. Within th

Agents

Large Language Models for Multi-Robot Systems: A Survey

arXiv:2502.03814v5 Announce Type: replace Abstract: The rapid advancement of Large Language Models (LLMs) has opened new possibilities in Multi-Robot Systems (MRS), enabling enhanced communication, ta

agentsarxiv-cs-ro

Latent Space Probing for Adult Content Detection in Video Generative Models

arXiv:2605.00874v1 Announce Type: new Abstract: The rapid proliferation of AI-powered video generation systems has introduced significant challenges in content moderation, particularly with respect to