Search: “research”

Multimodal Image Colorization: Quantifying the Impact of Text-Conditioned Guidance on Grayscale-to-Color Translation

arXiv:2606.20722v1 Announce Type: cross Abstract: Grayscale images are commonly found in historical photography restoration, medical imaging, and artistic media. However, automatically applying color

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muMatch: Foundation Models for Semi-supervised Learning and Domain Adaptation in EM

DGX agent

arXiv:2606.21605v1 Announce Type: new Abstract: Vision foundation models have substantially advanced computer vision, enabling state-of-the-art performance in zero- and few-shot settings. They have be

researcharxiv-cs-cv

23 Jun 2026

Music Playlist Captioning at Scale with Large Language Models

arXiv:2606.22460v1 Announce Type: cross Abstract: Music streaming services such as Deezer often recommend personalized playlists to users. Playlist captioning, which involves describing these playlist

MythraGen: Two-Stage Retrieval Augmented Art Generation Framework

arXiv:2606.22924v1 Announce Type: new Abstract: Text-to-image generation has seen rapid advancements, especially with the development of generative models. However, challenges remain in achieving high

NeoJaundice-AI: Smartphone-Based Neonatal Jaundice Detection Using Dual-Input Deep Learning and Synthetic Augmentation

arXiv:2606.20689v1 Announce Type: new Abstract: Neonatal jaundice (hyperbilirubinemia) is one of the most common conditions affecting newborns worldwide, with India alone recording roughly 15 million

Neural Architecture Search of Sample Reweighting Networks for Complex Distribution Shift

arXiv:2606.22991v1 Announce Type: new Abstract: Sample reweighting is a major approach to addressing distribution shifts, such as label noise and class imbalance. Meta-Weight-Net (MW-Net) is a promisi

Neural Networks as Linear Regression: An Introduction for Statisticians

arXiv:2606.23601v1 Announce Type: cross Abstract: Neural networks are a commonly used prediction tool in computer science and statistics. However, the barrier to entry of this interesting field remain

NeuroShield: A Device-Agnostic Foundation Model for EEG Authentication

arXiv:2606.20673v1 Announce Type: cross Abstract: A central challenge in EEG authentication is that models are typically tied to the acquisition settings in which they are trained. In particular, vari

New Smooth Loss functions for Robust Regression that Closely Approximate Absolute Error and Provide Improved Performance on Datasets With Significant Outliers

arXiv:2606.22068v1 Announce Type: new Abstract: The performance of supervised machine learning models is directly related to the quality of the training dataset. In particular, the presence of signifi

No Reference-Free Generalization in Quantum Machine Learning

arXiv:2606.22331v1 Announce Type: cross Abstract: Quantum machine learning is often motivated by the exponentially large state space of quantum systems, but this promise leaves a basic generalization

NoduLoCC2026: Lung Nodule Localization and Classification Contest from Chest X-Ray Images

arXiv:2606.21290v1 Announce Type: new Abstract: We propose NoduLoCC2026, a challenge on lung nodule detection and localization in chest X-ray images. We have provided a dataset for both tasks and rece

Non-Euclidean SGD for Structured Optimization: Unified Analysis and Improved Rates

arXiv:2511.11466v2 Announce Type: replace-cross Abstract: Recently, several instances of non-Euclidean SGD, including SignSGD, Lion, and Muon, have attracted significant interest from the optimization

Nonconvex-Nonconcave Min-Max Optimization with a Small Maximization Domain

arXiv:2110.03950v2 Announce Type: replace-cross Abstract: We study the problem of finding approximate first-order stationary points in optimization problems of the form min_{x in X} max_{y in Y} f(x,y

Null-Calibrated Conformal Selection via Target-Membership Scores

arXiv:2606.22336v1 Announce Type: cross Abstract: Conformal selection aims to identify test candidates whose unknown responses fall in a target region while controlling the false discovery rate. Exist

Null-Space Diffusion Distillation Unlocks Speed, Fidelity and Realism in Lensless Imaging

arXiv:2511.12024v3 Announce Type: replace Abstract: Lensless imaging reconstructs scenes from highly multiplexed measurements, resulting in a severely ill-posed inverse problem. In this work, we ident

Object-Centric Dataset Resources for Constrained-Data Image Generation and Augmentation

arXiv:2606.21113v1 Announce Type: new Abstract: Object-centric image generation is important in settings with few labeled examples, including pedestrian analysis in smart-city scenes, traffic-sign ins

Ocean4D: Generative Underwater 4D Reconstruction via Medium-Aware Video Diffusion

arXiv:2606.23298v1 Announce Type: new Abstract: Underwater 4D reconstruction remains challenging due to the coupling between degraded light transport in participating media and dynamic water variation

Odoriko: A Shape-Aware Multimodal Diffusion Framework for Human Motion

arXiv:2606.21135v1 Announce Type: new Abstract: Human motion generation has been widely studied across diverse input modalities, text, music, and video, and recent efforts have unified these into sing

Omega: Operator-based Mixture Ensemble for Generative Assimilation

arXiv:2606.20920v1 Announce Type: new Abstract: Characterizing non-Gaussian posterior distributions in partially observed high-dimensional nonlinear systems remains a fundamental challenge in data ass

On-Manifold Variational Learning with Heat-Kernel Priors

arXiv:2606.18658v2 Announce Type: replace Abstract: Learning unsupervised representations of medical imaging cohorts can reveal clinically meaningful prototypes without expert labels, which are often

On Quantum Perceptron Learning via Quantum Search

arXiv:2503.17308v2 Announce Type: replace-cross Abstract: With the growing interest in quantum machine learning, the perceptron, a fundamental building block in traditional machine learning, has emerg

On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA

arXiv:2606.21951v1 Announce Type: new Abstract: We study high-dimensional differentially private (DP) covariance estimation in the operator norm, and principal component analysis (PCA), under k-row-co

On the Sparsity-Storage-Accuracy Tradeoff in Parsimoniously Activated Dictionary Learning

arXiv:2606.22352v1 Announce Type: new Abstract: Dictionary learning has long been studied from both optimization and probabilistic perspectives. While formulations with element-wise sparsity regulariz

One-Step Flow Matching for Generative Modeling of Path-Dependent Physical Fields

arXiv:2606.22752v1 Announce Type: new Abstract: Physical simulations for intricate geometries with path-dependent constitutive models face difficulties due to the enormous computational cost they requ

Online Learning of Robust Legged Odometry with Minimal Exteroceptive Supervision

arXiv:2606.21669v1 Announce Type: new Abstract: Robust locomotion and navigation for legged robots relies heavily on dependable odometry. Traditional multi-sensor fusion for such state estimation requ

researcharxiv-cs-ro

OphthaDT: Generative Digital Twins for Forecasting Visual Acuity Trajectories in Ophthalmology

arXiv:2606.22101v1 Announce Type: cross Abstract: Precision medicine in ophthalmology requires accurate longitudinal predictions, but the fragmented nature of multimodal clinical data remains a barrie

OrthoMotion:Disentangling Camera and Subject Motion via Geometry Semantics Orthogonal Attention

arXiv:2606.22835v1 Announce Type: new Abstract: Controllable video generation demands independent command of the camera and the subject, yet 2D conditioning entangles them: camera- and object-induced

PaaF: Raising the perceived quality of INR-Based Image Compression

arXiv:2606.21655v1 Announce Type: cross Abstract: Implicit Neural Representations (INRs) have recently emerged as a promising paradigm for image compression, offering a fundamentally different approac

PACT: Preserving Anchored Cores in Task-vectors for Model Merging

arXiv:2606.18627v2 Announce Type: replace Abstract: Model merging has emerged as a training-free alternative to multi-task learning, aiming to combine multiple task-specific fine-tuned models into a s

Path-dependent program induction under resource constraints explains human sequence learning

arXiv:2606.20623v1 Announce Type: cross Abstract: How do people build abstract, reusable knowledge from sequential experience under bounded cognitive resources? To answer this question, we integrate r

Patient-Aware Contrastive Learning Preserves Per-Patient Structure in RR-Interval Representations

arXiv:2606.23570v1 Announce Type: new Abstract: Contrastive representation learning struggles on physiological signals when each subject contributes a distinct baseline pattern. If class differences o

PeLAP-A: Adaptive Latent Pruning for Lightweight Latent Diffusion Models

arXiv:2606.23086v1 Announce Type: new Abstract: Latent diffusion models achieve strong generative performance by operating in a compressed latent space produced by a variational autoencoder (VAE). How

PenduMorph: Development and Motion Analysis of Pendulum-Actuated Rolling Reconfigurable Spherical Robot with Magnetic-Coupling

arXiv:2606.22491v1 Announce Type: new Abstract: This paper presents 'PenduMorph', a wireless reconfigurable rolling spherical robot designed as a modular platform for enclosed locomotion and inter-mod

researcharxiv-cs-ro

PHAST-Net: Attention-Guided, Physics-Informed Network for Unified Estimation of Ideal Time-Frequency Representations

arXiv:2606.23665v1 Announce Type: cross Abstract: We introduce PHAST-Net, an attention-guided, physics-informed network for unified estimation of Ideal Time-Frequency Representations (ITFRs), spanning

Physics-Guided Fully Convolutional Spatiotemporal Learning Toward Digital-Twin-Enabled Microstructure Evolution Prediction

arXiv:2606.20983v1 Announce Type: new Abstract: Understanding and predicting microstructure evolution is central to materials design, yet purely data-driven spatiotemporal learning models often suffer

Physics-Guided Spatiotemporal State Space Modeling for Lookahead Molten Pool Segmentation in Laser Wire-Feed Welding

arXiv:2606.23028v1 Announce Type: new Abstract: Real-time weld-pool perception is critical for closed-loop control in laser wire-feed welding, where sensing, computation, and actuator response introdu

Physics-Preserving Latent Compression for Zero-Shot Resolution Transfer in 3D Turbulence

arXiv:2606.21781v1 Announce Type: cross Abstract: High-resolution turbulence modeling is essential for scientific computing, but remains constrained by the cost of direct numerical simulation and the

PIAvatar: Physically Interactive Avatars via Deformation Gradient Decoupling

arXiv:2606.21162v1 Announce Type: cross Abstract: 3D human avatars have shown impressive visual fidelity driven by pose-conditioned models, yet they still lack the physical ability required for intera

Plants appear to detect the patter of falling rain

MIT engineers have found the first direct evidence that plant seeds can sense sounds in nature: Rice submerged in shallow water germinated 30% to 40% more quickly when exposed to vibrations from water

researchmit-tech-review

Polynomial Dice Loss for Medical Image Segmentation

arXiv:2606.23373v1 Announce Type: new Abstract: Medical image segmentation is a fundamental task for medical image processing and computer-assisted intervention, yet data imbalance and small lesion de

Pre-Generation Hallucination Detection in Large Language Models via Soft-Target Attention Probing

arXiv:2606.21917v1 Announce Type: cross Abstract: Detecting hallucination risk before generation enables abstention, retrieval augmentation, and routing decisions without incurring the cost of decodin

Safety

Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model

arXiv:2408.06350v2 Announce Type: replace-cross Abstract: One debatable issue in traffic safety research is that cognitive load from sec-ondary tasks reduces primary task performance, such as driving.

safetyarxiv-cs-lg

Predicting High-Risk Colorectal Polyps in African Americans Using Pre-Colonoscopy Clinical Features: Machine Learning Model Development and Temporal Validation

arXiv:2606.21492v1 Announce Type: new Abstract: Risk stratification for advanced colorectal polyps typically relies on colonoscopy and/or pathology findings. However, there is growing interest in whet

Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology

arXiv:2606.18123v2 Announce Type: replace Abstract: Predicting immune biomarkers associated with the tumor immune microenvironment (TIME) is critical for advancing precision oncology, yet existing app

Predictive Feature Caching for Training-free Acceleration of Molecular Geometry Generation

arXiv:2510.04646v2 Announce Type: replace Abstract: Flow matching models generate high-fidelity molecular geometries but incur significant computational costs during inference, requiring hundreds of n

Prime Fourier Embeddings: A Principled Basis for Modular Arithmetic

arXiv:2606.23044v1 Announce Type: new Abstract: Numbers have algebraic structure that standard neural embeddings often fail to expose. We introduce Prime Fourier Embeddings (PFE), which encode integer

Privacy-Preserving Person Re-Identification from Temporal Sequences with Transformer and Hungarian Optimization

arXiv:2606.23230v1 Announce Type: new Abstract: Person re-identification (Re-ID) is a crucial task in surveillance and human behavior analysis, often used in public spaces such as transport hubs. Trad

Probabilistic Analysis of Least Squares, Orthogonal Projection, and QR Factorization Algorithms Subject to Gaussian Noise

arXiv:2409.18905v3 Announce Type: replace-cross Abstract: We consider the effect of Gaussian perturbations on least-squares residuals, orthogonal projections, and QR-type algorithms. The problem that