Search: “tutorials”

Defending Quantum Classifiers against Adversarial Perturbations through Quantum Autoencoders

arXiv:2604.28176v1 Announce Type: cross Abstract: Machine learning models can learn from data samples to carry out various tasks efficiently. When data samples are adversarially manipulated, such as b

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Tutorials

Efficient Sparse Selective-Update RNNs for Long-Range Sequence Modeling

DGX agent

arXiv:2603.02226v2 Announce Type: replace Abstract: Real-world sequential signals, such as audio or video, contain critical information that is often embedded within long periods of silence or noise.

tutorialsarxiv-cs-lg

1 May 2026

Electrostatic Clutch-Based Mechanical Multiplexer with Increased Force Capability

arXiv:2501.08469v4 Announce Type: replace Abstract: Robotic systems with many degrees of freedom (DoF) are constrained by the demands of dedicating a motor to each joint, and while mechanical multiple

tutorialsarxiv-cs-ro

Graph World Models: Concepts, Taxonomy, and Future Directions

arXiv:2604.27895v1 Announce Type: new Abstract: As one of the mainstream models of artificial intelligence, world models allow agents to learn the representation of the environment for efficient predi

Mapping the Methodological Space of Classroom Interaction Research: Scale, Duration, and Modality in an Age of AI

arXiv:2604.28098v1 Announce Type: new Abstract: Research on classroom interaction has long been divided between large-scale observation and in-depth ethnographic work. We propose a framework mapping t

Neural Aided Kalman Filtering for UAV State Estimation in Degraded Sensing Environments

arXiv:2604.28107v1 Announce Type: new Abstract: Accurate state estimation of nonlinear dynamical systems is fundamental to modern aerospace operations across air, sea, and space domains. Online tracki

Noise2Map: End-to-End Diffusion Model for Semantic Segmentation and Change Detection

arXiv:2604.27889v1 Announce Type: new Abstract: Semantic segmentation and change detection are two fundamental challenges in remote sensing, requiring models to capture either spatial semantics or tem

NORACL: Neurogenesis for Oracle-free Resource-Adaptive Continual Learning

arXiv:2604.27031v1 Announce Type: cross Abstract: In a continual learning setting, we require a model to be plastic enough to learn a new task and stable enough to not disturb previously learned capab

Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization

arXiv:2512.10955v2 Announce Type: replace Abstract: Visual concept personalization aims to transfer only specific image attributes, such as identity, expression, lighting, and style, into unseen conte

Predicting Atomistic Transitions with Transformers

arXiv:2603.06526v2 Announce Type: replace-cross Abstract: Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. Howe

Quantum Masked Autoencoders for Vision Learning

arXiv:2511.17372v2 Announce Type: replace-cross Abstract: Classical autoencoders are widely used to learn features of input data. To improve the feature learning, classical masked autoencoders extend

Reasoning over Object Descriptions Improves Coreference Resolution in Task-Based Dialogue Systems

arXiv:2604.27850v1 Announce Type: new Abstract: Task-based dialogue systems assist users in achieving specific goals, such as executing actions or retrieving information, through natural language inte

tutorialsarxiv-cs-cl

Transformer Semantic Genetic Programming for d-dimensional Symbolic Regression Problems

arXiv:2511.09416v2 Announce Type: replace Abstract: Transformer Semantic Genetic Programming (TSGP) is a semantic search approach that uses a pre-trained transformer model as a variation operator to g

UHR-Net: An Uncertainty-Aware Hypergraph Refinement Network for Medical Image Segmentation

arXiv:2604.28095v1 Announce Type: new Abstract: Accurate lesion segmentation is crucial for clinical diagnosis and treatment planning. However, lesions often resemble surrounding tissues and exhibit i

Upskilling with Generative AI: Practices and Challenges for Freelance Knowledge Workers

arXiv:2604.27231v1 Announce Type: cross Abstract: Freelance workers must continually acquire new skills to remain competitive in online labor markets, yet they lack the organizational training, mentor

VIPaint: Image Inpainting with Pre-Trained Diffusion Models via Variational Inference

arXiv:2411.18929v2 Announce Type: replace-cross Abstract: Diffusion probabilistic models learn to remove noise added during training, generating novel data (e.g., images) from Gaussian noise through s

A Data-Centric Framework for Intraoperative Fluorescence Lifetime Imaging for Glioma Surgical Guidance

arXiv:2604.26147v1 Announce Type: cross Abstract: Accurate intraoperative assessment of glioma infiltration is essential for maximizing tumor resection while preserving functional brain tissue. Fluore

A Virtual Mechanical Interaction Layer Enables Resilient Human-to-Robot Object Handovers

arXiv:2511.19543v2 Announce Type: replace Abstract: Object handover is a common form of interaction that is widely present in collaborative tasks. However, achieving it efficiently remains a challenge

tutorialsarxiv-cs-ro

Causal Learning with Neural Assemblies

arXiv:2604.26919v1 Announce Type: cross Abstract: Can Neural Assemblies -- groups of neurons that fire together and strengthen through co-activation -- learn the direction of causal influence between

CO-EVO: Co-evolving Semantic Anchoring and Style Diversification for Federated DG-ReID

arXiv:2604.26363v1 Announce Type: new Abstract: Federated domain generalization for person re-identification (FedDG-ReID) aims to collaboratively train a pedestrian retrieval model across multiple dec

Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolution

arXiv:2506.07179v2 Announce Type: replace-cross Abstract: Traffic prediction is a critical task in spatial-temporal forecasting with broad applications in travel planning and urban management. To mode

Evaluating the relationship between regularity and learnability in recursive numeral systems using Reinforcement Learning

arXiv:2602.21720v2 Announce Type: replace-cross Abstract: Human recursive numeral systems (i.e., counting systems such as English base-10 numerals), like many other grammatical systems, are highly reg

Explainable Representation of Finite-Memory Policies for POMDPs using Decision Trees

arXiv:2411.13365v2 Announce Type: replace Abstract: Partially Observable Markov Decision Processes (POMDPs) are a fundamental framework for decision-making under uncertainty and partial observability.

Generalized Disguise Makeup Presentation Attack Detection Using an Attention-Guided Patch-Based Framework

arXiv:2604.26025v1 Announce Type: new Abstract: Despite significant advances in facial recognition systems, they remain vulnerable to face presentation attacks. Among them, disguise makeup attacks are

Generative models on phase space

arXiv:2604.02415v2 Announce Type: replace-cross Abstract: Deep generative models such as diffusion and flow matching are powerful machine learning tools capable of learning and sampling from high-dime

HOI-aware Adaptive Network for Weakly-supervised Action Segmentation

arXiv:2604.26227v1 Announce Type: new Abstract: In this paper, we propose an HOI-aware adaptive network named AdaAct for weakly-supervised action segmentation. Most existing methods learn a fixed netw

Hyper Input Convex Neural Networks for Shape Constrained Learning and Optimal Transport

arXiv:2604.26942v1 Announce Type: new Abstract: We introduce Hyper Input Convex Neural Networks (HyCNNs), a novel neural network architecture designed for learning convex functions. HyCNNs combine the

Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data

arXiv:2604.26841v1 Announce Type: cross Abstract: When do language diffusion models memorize their training data, and how to quantitatively assess their true generative regime? We address these questi

Learning Sparse BRDF Measurement Samples from Image

arXiv:2604.26740v1 Announce Type: new Abstract: Accurate BRDF acquisition is important for realistic rendering, but dense gonioreflectometer measurements are slow and expensive. We study how to select

MetaSR: Content-Adaptive Metadata Orchestration for Generative Super-Resolution

arXiv:2604.26244v1 Announce Type: cross Abstract: We study generative super-resolution (SR) in real-world scenarios where content and degradations vary across domains, genres, and segments. For exampl

Mixture of Experts Framework in Machine Learning Interatomic Potentials for Atomistic Simulations

arXiv:2604.26143v1 Announce Type: cross Abstract: First-principles atomistic simulations are essential for understanding complex material phenomena but are fundamentally limited by their computational

Obliviator Reveals the Cost of Nonlinear Guardedness in Concept Erasure

arXiv:2603.07529v2 Announce Type: replace Abstract: Concept erasure aims to remove unwanted attributes, such as social or demographic factors, from learned representations, while preserving their task

Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time

arXiv:2604.26070v1 Announce Type: new Abstract: Causal inference in continuous-time sequential decision problems is challenged by hidden confounders. We show that, in latent state-space models with ti

Planar Gaussian Splatting with Bilinear Spatial Transformer for Wireless Radiance Field Reconstruction

arXiv:2604.25945v1 Announce Type: cross Abstract: Wireless radiance field (WRF) reconstruction aims to learn a continuous, queryable representation of radio frequency characteristics over 3D space and

PromptEvolver: Prompt Inversion through Evolutionary Optimization in Natural-Language Space

arXiv:2604.06061v2 Announce Type: replace Abstract: Text-to-image generation has progressed rapidly, but faithfully generating complex scenes requires extensive trial-and-error to find the exact promp

Robust Representation Learning through Explicit Environment Modeling

arXiv:2604.26128v1 Announce Type: cross Abstract: We consider learning from labeled data collected across multiple environments, where the data distribution may vary across these environments. This pr

Sparse Graph Learning from Sparse Data via Fiedler Number Maximization

arXiv:2604.26132v1 Announce Type: cross Abstract: We aim to learn a sparse and connected graph from sparse data, where the number of observations K can be substantially smaller than the signal dimensi

Speech Emotion Recognition Using MFCC Features and LSTM-Based Deep Learning Model

arXiv:2604.25938v1 Announce Type: cross Abstract: Speech Emotion Recognition (SER) is the use of machines to detect the emotional state of humans based on the speech, which is gaining importance in na

Towards Redundancy Reduction in Diffusion Models for Efficient Video Super-Resolution

arXiv:2509.23980v2 Announce Type: replace Abstract: Diffusion models have recently shown promising results for video super-resolution (VSR). However, directly adapting generative diffusion models to V

A New Kind of Network? Review and Reference Implementation of Neural Cellular Automata

arXiv:2604.24990v1 Announce Type: new Abstract: Stephen Wolfram proclaimed in his 2003 seminal work 'A New Kind Of Science' that simple recursive programs in the form of Cellular Automata (CA) are a p

Accelerating Regularized Attention Kernel Regression for Spectrum Cartography

arXiv:2604.25138v1 Announce Type: cross Abstract: Spectrum cartography reconstructs spatial radio fields from sparse and heterogeneous wireless measurements, underpinning many sensing and optimization

Accurate and Robust Generative Approach for Overcoming Data Sparsity and Imbalance in Landslide Modeling with A Tabular Foundation Model

arXiv:2604.25159v1 Announce Type: new Abstract: Landslide investigation relies on sufficient and well-balanced observational data influenced by geological, hydrological, and anthropogenic factors. Ava

Assessment of the quantitative impact of occlusal positioning splints on temporomandibular joint conditions

arXiv:2604.25322v1 Announce Type: new Abstract: A computational method for quantitative analysis of temporomandibular joint (TMJ) configuration using occlusal positioning splints is proposed and demon

Barriers to Universal Reasoning With Transformers (And How to Overcome Them)

arXiv:2604.25800v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) has been shown to empirically improve Transformers' performance, and theoretically increase their expressivity to Turing comple

tutorialsarxiv-cs-cl

C3G: Learning Compact 3D Representations with 2K Gaussians

arXiv:2512.04021v2 Announce Type: replace Abstract: Reconstructing and understanding 3D scenes from unposed sparse views in a feed-forward manner remains as a challenging task in 3D computer vision. R

Contrastive Image-Metadata Pre-Training for Materials Transmission Electron Microscopy

arXiv:2604.24909v1 Announce Type: new Abstract: The vast majority of transmission electron microscopy (TEM) data never gets published and ends up on a backup drive until deleted to free up space. Thes

DDA-Thinker: Decoupled Dual-Atomic Reinforcement Learning for Reasoning-Driven Image Editing

arXiv:2604.25477v1 Announce Type: new Abstract: Recent image editing models have achieved strong visual fidelity but often struggle with tasks requiring complex reasoning. To investigate and enhance t

Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity

arXiv:2603.20645v2 Announce Type: replace Abstract: Diffusion models have become a leading framework in generative modeling, yet their theoretical understanding -- especially for high-dimensional data