Search: “research”

A temporal deep learning framework for calibration of low-cost air quality sensors

arXiv:2604.21527v1 Announce Type: new Abstract: Low-cost air quality sensors (LCS) provide a practical alternative to expensive regulatory-grade instruments, making dense urban monitoring networks pos

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Research

A Tendon-Driven Wrist Abduction-Adduction Joint Improves Performance of a 5 DoF Upper Limb Exoskeleton -- Implementation and Experimental Evaluation

DGX agent

arXiv:2604.20898v1 Announce Type: new Abstract: Wrist function is essential in performing activities of daily living (ADLs). However, there is limited experimental evidence on the functional impact of

researcharxiv-cs-ro

24 Apr 2026

Accelerating Vision Transformers with Adaptive Patch Sizes

arXiv:2510.18091v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) partition input images into uniformly sized patches regardless of their content, resulting in long input sequence l

Accurate predictive model of band gap with selected important features based on explainable machine learning

arXiv:2503.04492v3 Announce Type: replace-cross Abstract: In the rapidly advancing field of materials informatics, nonlinear machine learning models have demonstrated exceptional predictive capabiliti

Achieving the Kesten-Stigum bound in the non-uniform hypergraph stochastic block model

arXiv:2604.20907v1 Announce Type: cross Abstract: We study the community detection problem in the non-uniform hypergraph stochastic block model (HSBM), where hyperedges of varying sizes coexist. This

Active Data

arXiv:2604.21044v1 Announce Type: new Abstract: In some complex domains, certain problem-specific decompositions can provide advantages over monolithic designs by enabling comprehension and specificat

Active Learning for Planet Habitability Classification under Extreme Class Imbalance

arXiv:2602.23666v2 Announce Type: replace-cross Abstract: The increasing size and heterogeneity of exoplanet catalogs have made systematic habitability assessment challenging, particularly given the e

Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations

arXiv:2604.21018v1 Announce Type: new Abstract: While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from

Addressing divergent representations from causal interventions on neural networks

arXiv:2511.04638v5 Announce Type: replace-cross Abstract: A common approach to mechanistic interpretability is to causally manipulate model representations via targeted interventions in order to under

Addressing Image Authenticity When Cameras Use Generative AI

arXiv:2604.21879v1 Announce Type: cross Abstract: The ability of generative AI (GenAI) methods to photorealistically alter camera images has raised awareness about the authenticity of images shared on

AI for software engineering: from probable to provable

arXiv:2511.23159v2 Announce Type: replace-cross Abstract: Vibe coding, the much-touted use of AI techniques for programming, faces two overwhelming obstacles: the difficulty of specifying goals ('prom

Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformers

arXiv:2507.15753v2 Announce Type: replace-cross Abstract: Generative machine learning models have revolutionized material discovery by capturing complex structure-property relationships, yet extending

An effective variant of the Hartigan k-means algorithm

arXiv:2604.21798v1 Announce Type: new Abstract: The k-means problem is perhaps the classical clustering problem and often synonymous with Lloyd's algorithm (1957). It has become clear that Hartigan's

Analytical FFN-to-MoE Restructuring via Activation Pattern Analysis

arXiv:2502.04416v3 Announce Type: replace-cross Abstract: Scaling large language models (LLMs) improves performance but significantly increases inference costs, with feed-forward networks (FFNs) consu

Anatomy-Aware Text-Visual Fusion with Dual-Perspective Prompts for Fine-Grained Lumbar Spine Segmentation

arXiv:2504.03476v2 Announce Type: replace Abstract: Accurate lumbar spine segmentation is crucial for diagnosing spinal disorders. Existing methods typically use coarse-grained segmentation strategies

Artificial intelligence for methane detection: from continuous monitoring to verified mitigation

arXiv:2511.21777v2 Announce Type: replace Abstract: Methane is a potent greenhouse gas, responsible for roughly 30% of warming since pre-industrial times. A small number of large point sources account

Assessing Emulator Design and Training for Modal Aerosol Microphysics Parameterizations in E3SMv2

arXiv:2604.21233v1 Announce Type: cross Abstract: Toward the goal of using Scientific Machine Learning (SciML) emulators to improve the numerical representation of aerosol processes in global atmosphe

ATLAS: AI-Assisted Threat-to-Assertion Learning for System-on-Chip Security Verification

arXiv:2603.01170v2 Announce Type: replace-cross Abstract: This work presents ATLAS, an LLM-driven framework that bridges standardized threat modeling and property-based formal verification for System-

ATOM: A Pretrained Neural Operator for Multitask Molecular Dynamics

arXiv:2510.05482v2 Announce Type: replace Abstract: Molecular dynamics (MD) simulations underpin modern computational drug discovery, materials science, and biochemistry. Recent machine learning model

Attention-based multiple instance learning for predominant growth pattern prediction in lung adenocarcinoma wsi using foundation models

arXiv:2604.21530v1 Announce Type: cross Abstract: Lung adenocarcinoma (LUAD) grading depends on accurately identifying growth patterns, which are indicators of prognosis and can influence treatment de

Back to Source: Open-Set Continual Test-Time Adaptation via Domain Compensation

arXiv:2604.21772v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) aims to mitigate distributional shifts between training and test domains during inference time. However, existing TTA methods

BackPlay: Head-Only Look-Back Self-Correction for Diffusion Language Models

arXiv:2601.06428v3 Announce Type: replace Abstract: Diffusion Language Models (DLMs) decode multiple tokens in parallel, but aggressive multi-token decoding amplifies cross-token dependency errors and

Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions

arXiv:2604.21849v1 Announce Type: cross Abstract: Bayesian Optimal Experimental Design (BOED) provides a rigorous framework for decision-making tasks in which data acquisition is often the critical bo

Beyond the Frame: Generating 360 Panoramic Videos from Perspective Videos

arXiv:2504.07940v3 Announce Type: replace Abstract: 360{eg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the 'tunnel vision' of standard cameras, their

Bridging the Training-Deployment Gap: Gated Encoding and Multi-Scale Refinement for Efficient Quantization-Aware Image Enhancement

arXiv:2604.21743v1 Announce Type: new Abstract: Image enhancement models for mobile devices often struggle to balance high output quality with the fast processing speeds required by mobile hardware. W

Calibeating Prediction-Powered Inference

arXiv:2604.21260v1 Announce Type: cross Abstract: We study semisupervised mean estimation with a small labeled sample, a large unlabeled sample, and a black-box prediction model whose output may be mi

Causal Disentanglement for Full-Reference Image Quality Assessment

arXiv:2604.21654v1 Announce Type: cross Abstract: Existing deep network-based full-reference image quality assessment (FR-IQA) models typically work by performing pairwise comparisons of deep features

Certified Coil Geometry Learning for Short-Range Magnetic Actuation and Spacecraft Docking Application

arXiv:2507.03806v3 Announce Type: replace-cross Abstract: This paper presents a learning-based framework for approximating an exact magnetic-field interaction model, supported by both numerical and ex

ChessArena: A Chess Testbed for Evaluating Strategic Reasoning Capabilities of Large Language Models

arXiv:2509.24239v4 Announce Type: replace-cross Abstract: Recent large language models (LLMs) have shown strong reasoning capabilities. However, a critical question remains: do these models possess ge

climt-paraformer: Stable Emulation of Convective Parameterization using a Temporal Memory-aware Transformer

arXiv:2604.21085v1 Announce Type: cross Abstract: Accurate representation of moist convective sub-grid-scale processes remains a major challenge in global climate models, as traditional parameterizati

Clinical Evaluation of a Tongue-Controlled Wrist Abduction-Adduction Assistance in a 6-DoF Upper-Limb Exoskeleton for Individuals with ALS and SCI

arXiv:2604.20967v1 Announce Type: new Abstract: Upper-limb exoskeletons (ULEs) have the potential to restore functional independence in individuals with severe motor impairments; however, the clinical

researcharxiv-cs-ro

Clinically-Informed Modeling for Pediatric Brain Tumor Classification from Whole-Slide Histopathology Images

arXiv:2604.21060v1 Announce Type: new Abstract: Accurate diagnosis of pediatric brain tumors, starting with histopathology, presents unique challenges for deep learning, including severe data scarcity

CoFEE: Reasoning Control for LLM-Based Feature Discovery

arXiv:2604.21584v1 Announce Type: new Abstract: Feature discovery from complex unstructured data is fundamentally a reasoning problem: it requires identifying abstractions that are predictive of a tar

Component-Based Out-of-Distribution Detection

arXiv:2604.21546v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection requires sensitivity to subtle shifts without overreacting to natural In-Distribution (ID) diversity. However, from

Context Unrolling in Omni Models

arXiv:2604.21921v1 Announce Type: new Abstract: We present Omni, a unified multimodal model natively trained on diverse modalities, including text, images, videos, 3D geometry, and hidden representati

Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation

arXiv:2303.03237v4 Announce Type: replace-cross Abstract: Sampling from Gibbs distributions and computing their log-partition function are fundamental tasks in statistics, machine learning, and statis

Cosmological Analysis with Calibrated Neural Quantile Estimation and Approximate Simulators

arXiv:2411.14748v2 Announce Type: replace-cross Abstract: A major challenge in extracting information from current and upcoming surveys of cosmological Large-Scale Structure (LSS) is the limited avail

Cross-Distribution Diffusion Priors-Driven Iterative Reconstruction for Sparse-View CT

arXiv:2509.13576v2 Announce Type: replace-cross Abstract: Sparse-View CT (SVCT) reconstruction enhances temporal resolution and reduces radiation dose, yet its clinical use is hindered by artifacts du

DCMorph: Face Morphing via Dual-Stream Cross-Attention Diffusion

arXiv:2604.21627v1 Announce Type: new Abstract: Advancing face morphing attack techniques is crucial to anticipate evolving threats and develop robust defensive mechanisms for identity verification sy

Deep kernel video approximation for unsupervised action segmentation

arXiv:2604.21572v1 Announce Type: new Abstract: This work focuses on per-video unsupervised action segmentation, which is of interest to applications where storing large datasets is either not possibl

Dementia classification from spontaneous speech using wrapper-based feature selection

arXiv:2502.03484v2 Announce Type: replace-cross Abstract: Dementia encompasses a group of syndromes that impair cognitive functions such as memory, reasoning, and the ability to perform daily activiti

DiffNR: Diffusion-Enhanced Neural Representation Optimization for Sparse-View 3D Tomographic Reconstruction

arXiv:2604.21518v1 Announce Type: cross Abstract: Neural representations (NRs), such as neural fields and 3D Gaussians, effectively model volumetric data in computed tomography (CT) but suffer from se

Dilated CNNs for Periodic Signal Processing: A Low-Complexity Approach

arXiv:2604.21651v1 Announce Type: cross Abstract: Denoising of periodic signals and accurate waveform estimation are core tasks across many signal processing domains, including speech, music, medical

Distributed Associative Memory via Online Convex Optimization

arXiv:2509.22321v2 Announce Type: replace Abstract: An associative memory (AM) enables cue-response recall, and associative memorization has recently been noted to underlie the operation of modern neu

Do Masked Autoencoders Improve Downhole Prediction? An Empirical Study on Real Well Drilling Data

arXiv:2604.20909v1 Announce Type: new Abstract: Downhole drilling telemetry presents a fundamental labeling asymmetry: surface sensor data are generated continuously at 1~Hz, while labeled downhole me

Early Detection of Latent Microstructure Regimes in Limit Order Books

arXiv:2604.20949v1 Announce Type: new Abstract: Limit order books can transition rapidly from stable to stressed conditions, yet standard early-warning signals such as order flow imbalance and short-t

Efficient Logic Gate Networks for Video Copy Detection

arXiv:2604.21694v1 Announce Type: cross Abstract: Video copy detection requires robust similarity estimation under diverse visual distortions while operating at very large scale. Although deep neural

Enhancing Online Recruitment with Category-Aware MoE and LLM-based Data Augmentation

arXiv:2604.21264v1 Announce Type: new Abstract: Person-Job Fit (PJF) is a critical component for online recruitment. Existing approaches face several challenges, particularly in handling low-quality j