Search: “applications”

Scalable Krylov Subspace Methods for Generalized Mixed-Effects Models with Crossed Random Effects

arXiv:2505.09552v3 Announce Type: replace-cross Abstract: Mixed-effects models are widely used to model data with hierarchical grouping structures and high-cardinality categorical predictor variables.

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Research

Scalable Solution of the Stochastic Multi-path Traveling Salesman Problem via Neural Networks

DGX agent

arXiv:2605.14662v1 Announce Type: cross Abstract: The multi-path Traveling Salesman Problem with stochastic travel costs arises in hybrid vehicle routing applications designed for Smart City and City

researcharxiv-cs-lg

15 May 2026

SCRWKV: Ultra-Compact Structure-Calibrated Vision-RWKV for Topological Crack Segmentation

arXiv:2605.14926v1 Announce Type: new Abstract: Achieving pixel-level accurate segmentation of structural cracks across diverse scenarios remains a formidable challenge. Existing methods face signific

SEDGE: Structural Extrapolated Data Generation

arXiv:2604.02482v2 Announce Type: replace Abstract: This paper aims to address the challenge of data generation beyond the training data and proposes a framework for Structural Extrapolated Data GEner

Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

arXiv:2510.16196v2 Announce Type: replace-cross Abstract: Understanding how the brain encodes visual information is a central challenge in neuroscience and machine learning. A promising approach is to

Self-Regulated Learning in Essay Writing: Consistency of Strategies and Impact on Outcomes

arXiv:2605.14228v1 Announce Type: cross Abstract: Background: Abilities for effective self-regulated learning (SRL) are critical for lifelong learning, particularly during adolescence when these skill

Silent Neuron Theory and Plasticity Preservation for Deep Reinforcement Learning in Adaptive Video Streaming

arXiv:2505.01584v3 Announce Type: replace-cross Abstract: Adaptive video streaming optimizes Quality of Experience (QoE) metrics by selecting appropriate bitrates according to varying network bandwidt

SoFFT: Spatial Fourier Transform for Modeling Continuum Soft Robots

arXiv:2502.17347v2 Announce Type: replace Abstract: Continuum soft robots, composed of flexible materials, exhibit theoretically infinite degrees of freedom, enabling notable adaptability in unstructu

applicationsarxiv-cs-ro

Spectral Analysis of Fake News Propagation

arXiv:2605.13861v1 Announce Type: cross Abstract: The propagation structure of fake news has been shown to be an important cue for detecting it; yet, existing propagation-based fake news detection met

SuperADD: Training-free Class-agnostic Anomaly Segmentation -- CVPR 2026 VAND 4.0 Workshop Challenge Industrial Track

arXiv:2605.14808v1 Announce Type: new Abstract: Visual anomaly detection (AD) for industrial inspection is a highly relevant task in modern production environments. The problem becomes particularly ch

SurF: A Generative Model for Multivariate Irregular Time Series Forecasting

arXiv:2605.14069v1 Announce Type: new Abstract: Irregularly sampled multivariate event streams remain a stubbornly difficult modality for generative modeling: tokenization-based approaches break down

SyncLight: Single-Edit Multi-View Relighting

arXiv:2601.16981v2 Announce Type: replace Abstract: We present SyncLight, a method to enable consistent, parametric control over light sources across multiple uncalibrated views of a static scene cond

TabClustPFN: A Prior-Fitted Network for Tabular Data Clustering

arXiv:2601.21656v3 Announce Type: replace Abstract: Clustering tabular data is a fundamental yet challenging problem due to heterogeneous feature types, diverse data-generating mechanisms, and the abs

The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot

arXiv:2410.02091v3 Announce Type: replace-cross Abstract: Generative artificial intelligence (AI) facilitates content production and enhances ideation capabilities, which can significantly influence d

The Potential of Convolutional Neural Networks for Cancer Detection

arXiv:2412.17155v4 Announce Type: replace Abstract: Early detection is crucial for successful cancer treatment and increasing survivability rates, particularly in the most common forms. Ten different

Model Releases

TILBench: A Systematic Benchmark for Tabular Imbalanced Learning Across Data Regimes

model-releasesarxiv-cs-lg

arXiv:2605.14915v1 Announce Type: new Abstract: Imbalanced learning remains a fundamental challenge in tabular data applications. Despite decades of research and numerous proposed algorithms, a system

TOPOS: High-Fidelity and Efficient Industry-Grade 3D Head Generation

arXiv:2605.14594v1 Announce Type: new Abstract: High-fidelity 3D head generation plays a crucial role in the film, animation and video game industries. In industrial pipelines, studios typically enfor

What if Tomorrow is the World Cup Final? Counterfactual Time Series Forecasting with Textual Conditions

arXiv:2605.14422v1 Announce Type: new Abstract: Time series forecasting has become increasingly critical in real-world scenarios, where future sequences are influenced not only by historical patterns

A Hybrid Tucker-LSTM Tensor Network Model for SOC Prediction in Electric Vehicles

arXiv:2605.13200v1 Announce Type: new Abstract: Accurate state of charge estimation is critical for the success of electric vehicle battery management strategies, but it is well known that conventiona

A Unified Three-Stage Machine Learning Framework for Diabetes Detection, Subtype Discrimination, and Cognitive-Metabolic Hypothesis Testing

arXiv:2605.13464v1 Announce Type: new Abstract: Diabetes mellitus affects over 537 million adults worldwide and remains a major challenge in preventive healthcare. Existing machine-learning studies pr

Conditional Compatibility Learning for Context-Dependent Anomaly Detection

arXiv:2601.22868v3 Announce Type: replace Abstract: Anomaly detection usually assumes that abnormality is an intrinsic property of an observation. A defect is a defect, and a rare object is rare, rega

Decoupled and Divergence-Conditioned Prompt for Multi-domain Dynamic Graph Foundation Models

arXiv:2605.13540v1 Announce Type: cross Abstract: Dynamic graphs are ubiquitous in real-world systems, and building generalizable dynamic Graph Foundation Models has become a frontier in graph learnin

DeePen: Penetration Testing for Audio Deepfake Detection

arXiv:2502.20427v3 Announce Type: replace-cross Abstract: Deepfakes - manipulated or forged audio and video media - pose significant security risks to individuals, organizations, and society at large.

Distinguishing performance gains from learning when using generative AI

arXiv:2605.13731v1 Announce Type: new Abstract: Generative artificial intelligence (AI) is increasingly being integrated into education, where it can boost learners' performance. However, these uses d

Do Heavy Tails Help Diffusion? On the Subtle Trade-off Between Initialization and Training

arXiv:2605.13175v1 Announce Type: new Abstract: Recent works have proposed incorporating heavy-tailed (HT) noise into diffusion- and flow-based generative models, with the goals of better recovering t

Efficient Generative Prediction for EHR Foundation Models: The SCOPE and REACH Estimators

arXiv:2602.03730v2 Announce Type: replace-cross Abstract: Generative foundation models trained on tokenized electronic health record (EHR) timelines show promise for clinical outcome prediction via Mo

EvObj: Learning Evolving Object-centric Representations for 3D Instance Segmentation without Scene Supervision

arXiv:2605.13152v1 Announce Type: cross Abstract: We introduce EvObj for unsupervised 3D instance segmentation that bridges the geometric domain gap between synthetic pretraining data and real-world p

Model Releases

Fast and effective algorithms for fair clustering at scale

model-releasesarxiv-cs-lg

arXiv:2605.13759v1 Announce Type: new Abstract: Clustering is an unsupervised machine learning task that consists of identifying groups of similar objects. It has numerous applications and is increasi

It's not the Language Model, it's the Tool: Deterministic Mediation for Scientific Workflows

arXiv:2605.13245v1 Announce Type: new Abstract: Language models can produce convincing scientific analyses, but repeated generations on the same data do not guarantee the same result. A researcher may

KVServe: Service-Aware KV Cache Compression for Communication-Efficient Disaggregated LLM Serving

arXiv:2605.13734v1 Announce Type: cross Abstract: LLMs are widely adopted in production, pushing inference systems to their limits. Disaggregated LLM serving (e.g., PD separation and KV state disaggre

Language Model Networks: Supervision-Efficient Learning through Dense Communication

arXiv:2505.12741v2 Announce Type: replace Abstract: Language models are increasingly used not only as standalone predictors but also as components in larger inference systems, from test-time reasoning

Learning Perturbations to Extrapolate Your LLM

arXiv:2605.13284v1 Announce Type: cross Abstract: Recent advancements in large language models demonstrate that injecting perturbations can substantially enhance extrapolation performance. However, cu

Safety

Learning Transferable Latent User Preferences for Human-Aligned Decision Making

arXiv:2605.12682v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as reasoning modules in many applications. While they are efficient in certain tasks, LLMs often stru

safetyarxiv-cs-ai

MILM: Large Language Models for Multimodal Irregular Time Series with Informative Sampling

arXiv:2605.13711v1 Announce Type: new Abstract: Multimodal irregular time series (MITS) consist of asynchronous and irregularly sampled observations from heterogeneous numerical and textual channels.

Model Releases

Pattern-Enhanced RT-DETR for Multi-Class Battery Detection

model-releasesarxiv-cs-cv

arXiv:2605.13670v1 Announce Type: new Abstract: Accurate and efficient battery detection is increasingly important for applications in electronic waste recycling, industrial quality control, and autom

Progressively Sampled Equality-Constrained Optimization

arXiv:2510.00417v2 Announce Type: replace-cross Abstract: An algorithm is proposed, analyzed, and tested for solving continuous nonlinear-equality-constrained optimization problems where the objective

Safety

Quantifying LLM Safety Degradation Under Repeated Attacks Using Survival Analysis

arXiv:2605.12869v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in a wide range of applications, yet remain vulnerable to adversarial jailbreak attacks that ci

safetyarxiv-cs-ai

Quantifying Potential Observation Missingness in Inverse Reinforcement Learning

arXiv:2605.12831v1 Announce Type: new Abstract: Inverse reinforcement learning (IRL), which infers reward functions from demonstrations, is a valuable tool for modeling and understanding decision-maki

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

Realtime-VLA FLASH: Speculative Inference Framework for Diffusion-based VLAs

arXiv:2605.13778v1 Announce Type: cross Abstract: Diffusion-based vision-language-action models (dVLAs) are promising for embodied intelligence but are fundamentally limited in real-time deployment by

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations

arXiv:2507.00990v3 Announce Type: replace-cross Abstract: This work introduces Robots Imitating Generated Videos (RIGVid), a system that enables robots to perform complex manipulation tasks--such as p

Robust Sequential Experimental Design for A/B Testing

arXiv:2605.12899v1 Announce Type: cross Abstract: Experimental design has emerged as a powerful approach for improving the sample efficiency of A/B testing, yet existing designs rely critically on cor

RotVLA: Rotational Latent Action for Vision-Language-Action Model

arXiv:2605.13403v1 Announce Type: cross Abstract: Latent Action Models (LAMs) have emerged as an effective paradigm for handling heterogeneous datasets during Vision-Language-Action (VLA) model pretra

Research

Sample-Efficient Optimisation over the Outputs of Generative Models

arXiv:2509.23800v3 Announce Type: replace-cross Abstract: Modern generative AI models, such as diffusion and flow matching models, can sample from rich data distributions. However, many applications,

researcharxiv-cs-lg

Scale over Preference: The Impact of AI-Generated Content on Online Content Ecology

arXiv:2604.01690v2 Announce Type: replace Abstract: The rapid proliferation of Artificial Intelligence-Generated Content (AIGC) is fundamentally restructuring online content ecologies, necessitating a

SSDA: Bridging Spectral and Structural Gaps via Dual Adaptation for Vision-Based Time Series Forecasting

arXiv:2605.12550v1 Announce Type: cross Abstract: Large vision models (LVMs) have recently proven to be surprisingly effective time series forecasters, simply by rendering temporal data as images. Thi

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

Taming the Long Tail: Rebalancing Adversarial Training via Adaptive Perturbation

arXiv:2605.13395v1 Announce Type: cross Abstract: Deep neural networks are highly vulnerable to adversarial examples, i.e.,small perturbations that can significantly degrade model performance. While a