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arXiv:2605.21388v1 Announce Type: new Abstract: Despite the remarkable empirical success of generative models, the available theory on their statistical accuracy in scientific computing remains largel

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One-Step Distillation of Discrete Diffusion Image Generators via Fixed-Point Iteration

DGX agent

arXiv:2605.21484v1 Announce Type: new Abstract: Discrete diffusion models excel at visual synthesis but rely on slow, iterative decoding. Existing single-step distillation methods attempt to bypass th

local-aiarxiv-cs-cv

21 May 2026

Local Ai

Online 3D Multi-Camera Perception through Robust 2D Tracking and Depth-based Late Aggregation

arXiv:2509.09946v2 Announce Type: replace Abstract: Multi-Target Multi-Camera Tracking (MTMC) is an essential computer vision task for automating large-scale surveillance. With camera calibration and

local-aiarxiv-cs-cv

Online Conformal Prediction with Corrupted Feedback

arXiv:2605.20515v1 Announce Type: new Abstract: Modern artificial intelligence systems require calibrated uncertainty estimates that remain reliable in sequential and non-stationary environments. Onli

applicationsarxiv-cs-lg

PointACT: Vision-Language-Action Models with Multi-Scale Point-Action Interaction

arXiv:2605.21414v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong potential for general-purpose robotic manipulation by leveraging large pretrained vision-languag

safetyarxiv-cs-cv

PrefixWall: Mitigating Prefix Caching Side Channels in Shared LLM Systems

arXiv:2603.10726v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) rely on optimizations like Automatic Prefix Caching (APC) to accelerate inference. APC works by reusing previousl

Q-ARVD: Quantizing Autoregressive Video Diffusion Models

arXiv:2605.21072v1 Announce Type: new Abstract: Autoregressive video diffusion models (ARVDs) have emerged as a promising architecture for streaming video generation, paving the way for real-time inte

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation

arXiv:2605.20801v1 Announce Type: new Abstract: Adaptive robot navigation in dynamic environments requires policies that can reach the target reliably while producing efficient and stable trajectories

safetyarxiv-cs-ro

Q-SYNTH: Hybrid Quantum-Classical Adversarial Augmentation for Imbalanced Fraud Detection

arXiv:2605.21164v1 Announce Type: new Abstract: Credit card fraud detection is fundamentally challenged by extreme class imbalance, where fraudulent transactions are rare yet operationally critical. T

Quadratic Characterizations for Reachability Analysis of Neural Networks

arXiv:2605.20482v1 Announce Type: new Abstract: Quadratic constraints (QCs) are widely used to characterize nonlinearities and uncertainties, but generic analytical characterizations can be conservati

Quantifying Hyperparameter Transfer and the Importance of Embedding Layer Learning Rate

model-releasesarxiv-cs-lg

arXiv:2605.21486v1 Announce Type: new Abstract: Hyperparameter transfer allows extrapolating optimal optimization hyperparameters from small to large scales, making it critical for training large lang

QwenSafe: Multimodal Content Rating Description Identification via Preference-Aligned VLMs

model-releasesarxiv-cs-cv

arXiv:2605.20584v1 Announce Type: new Abstract: Mobile app marketplaces require developers to disclose standardized content rating descriptors (CRDs) to inform users about potentially sensitive or res

rePIRL: Learn PRM with Inverse RL for LLM Reasoning

arXiv:2602.07832v2 Announce Type: replace Abstract: Process rewards have been widely used in deep reinforcement learning to improve training efficiency, reduce variance, and prevent reward hacking. In

Rethinking Cross-Layer Information Routing in Diffusion Transformers

arXiv:2605.20708v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have become a de facto backbone of modern visual generation, and nearly every major axis of their design -- tokenization,

safetyarxiv-cs-cv

Retrospective Sparse Attention for Efficient Long-Context Generation

arXiv:2508.09001v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed in long-context tasks such as reasoning, code generation, and multi-turn dialogue. However, i

researcharxiv-cs-cl

Robust Recommendation from Noisy Implicit Feedback: A GMM-Weighted Bayes-label Transition Matrix Framework

arXiv:2605.20721v1 Announce Type: new Abstract: Learning from implicit feedback in recommender systems is fundamentally challenged by pervasive label noise. While conventional denoising approaches oft

Safety-Critical Control for Smoothed Implicit Contact Dynamics

model-releasesarxiv-cs-ro

arXiv:2605.21138v1 Announce Type: new Abstract: Smoothed implicit contact dynamics enables gradient-based planning and control for contact-rich tasks without predefined mode sequences. However, safety

Seeing Through Fog: Towards Fog-Invariant Action Recognition

model-releasesarxiv-cs-cv

arXiv:2605.20645v1 Announce Type: new Abstract: Foggy conditions are commonly encountered in real-world applications; however, existing action recognition approaches typically assume favorable weather

Shiny Stories, Hidden Struggles: Investigating the Representation of Disability Through the Lens of LLMs

arXiv:2605.20191v1 Announce Type: new Abstract: Modern Large Language Models (LLMs) have recently attracted much attention for their ability to simulate human behavior and generate text that reflects

safetyarxiv-cs-cl

Testing Support Size More Efficiently Than Learning Histograms

arXiv:2410.18915v4 Announce Type: replace-cross Abstract: Consider two problems about an unknown probability distribution p: 1. How many samples from p are required to test if p is supported on n elem

Text Analytics Evaluation Framework: A Case Study on LLMs and Social Media

model-releasesarxiv-cs-cl

arXiv:2605.21338v1 Announce Type: new Abstract: LLMs have demonstrated exceptional proficiency in a wide range of NLP tasks. However, a notable gap remains in practical data analysis scenarios, partic

Time-To-Reach Separation and Safety Filtering for Safe, Fair, and Efficient Multi-Agent Coordination

arXiv:2605.20625v1 Announce Type: cross Abstract: Advanced Air Mobility (AAM) operations are expected to significantly increase aerial traffic in urban airspace, requiring autonomous traffic managemen

safetyarxiv-cs-ro

Today we release a study on decoupling the benefits of subword tokenization for language model training, by simulating each suspected benefi…

model-releasesnous-research--x

Today we release a study on decoupling the benefits of subword tokenization for language model training, by simulating each suspected benefit one at a time inside a 1.7B byte-level pretraining pipelin

torchtune: PyTorch native post-training library

arXiv:2605.21442v1 Announce Type: new Abstract: Modern LLMs typically require multistage training pipelines to achieve strong downstream performance, with post-training serving as the main interface f

Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G

arXiv:2605.21395v1 Announce Type: cross Abstract: The proliferation of emerging applications, such as autonomous driving and immersive experiences, demands cellular networks that are not only faster,

agentsarxiv-cs-lg

Towards the Anonymization of the Language Modeling

arXiv:2501.02407v3 Announce Type: replace Abstract: Rapid advances in Natural Language Processing (NLP) have revolutionized many fields, including healthcare. However, these advances raise significant

applicationsarxiv-cs-cl

Tunable MAGMAX: Preference-Aware Model Merging for Continual Learning

model-releasesarxiv-cs-lg

arXiv:2605.20803v1 Announce Type: new Abstract: Continual learning (CL) aims to train models sequentially on multiple tasks while mitigating catastrophic forgetting of previously learned knowledge. Re

UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models

arXiv:2504.13109v2 Announce Type: replace Abstract: Flow matching models have emerged as a strong alternative to diffusion models, but existing inversion and editing methods designed for diffusion are

US issues $2B+ in grants to IBM, others for quantum computing initiatives

The U.S. Commerce Department will issue 2.013 billion in grants to IBM Corp., GlobalFoundries Inc. and seven other tech firms to finance quantum computing initiatives. The Wall Street Journal reported

applicationssiliconangle

USV: Towards Understanding the User-generated Short-form Videos

arXiv:2605.20838v1 Announce Type: new Abstract: Several large-scale video datasets have been published these years and have advanced the area of video understanding. However, the newly emerged user-ge

Validating Navmesh using Geometry: Voxel-Based Analysis with Prioritized Exploration

arXiv:2605.21397v1 Announce Type: cross Abstract: Navigation mesh (Navmesh) inconsistencies affect the player experience by directly impacting the navigation systems used by non-playable characters (N

applicationsarxiv-cs-ro

Verifiable Error Bounds for Physics-Informed Neural Network Solutions of Lyapunov and Hamilton-Jacobi-Bellman Equations

arXiv:2603.19545v2 Announce Type: replace-cross Abstract: Many core problems in nonlinear systems analysis and control can be recast as solving partial differential equations (PDEs) such as Lyapunov a

Vision Transformers and Convolutional Neural Networks for Land Use Scene Classification

model-releasesarxiv-cs-cv

arXiv:2605.21268v1 Announce Type: new Abstract: Land Use Scene Classification (LUSC) from remote sensing imagery plays a critical role in environmental monitoring, urban planning, and sustainable reso

WaveGraphNet: Physics-Consistent Guided-Wave Damage Localization through Coupled Inverse-Forward Graph Learning

model-releasesarxiv-cs-lg

arXiv:2605.20311v1 Announce Type: new Abstract: Guided-wave structural health monitoring enables damage localization in composite plates using sparse networks of bonded piezoelectric transducers. Howe

What we find most useful about this study is the decomposition. For byte-level pretraining, the ordering is throughput first and boundary si…

What we find most useful about this study is the decomposition. For byte-level pretraining, the ordering is throughput first and boundary signal second; the boundary benefit can be recovered without a

researchnous-research--x

Why Latent Actions Fail, and How to Prevent It

arXiv:2605.20223v1 Announce Type: new Abstract: Latent action models (LAMs) aim to learn action-like representations from unlabeled videos by compressing frame-to-frame changes. The frames of in-the-w

agentsarxiv-cs-cv

Tutorials

WiXus: A Wheeled-Legged Robot with Wire-Driven Environmental Utilizing to Integrate Mobility and Manipulation

arXiv:2605.20932v1 Announce Type: new Abstract: Wheeled-legged robots, which have wheels at their feet and achieve high mobility by coordinating wheel drive and leg drive, have been developed. These r

tutorialsarxiv-cs-ro

A Data-Driven Approach to Idiomaticity Based on Experts' Criteria in Theoretical Linguistics

arXiv:2605.19575v1 Announce Type: new Abstract: The article observes data analysis of 286 multi-word expressions (MWEs) based on 16 lexical, grammatical and other criteria described in theoretical boo

researcharxiv-cs-cl

A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond

arXiv:2510.19382v2 Announce Type: replace-cross Abstract: Understanding the dynamics of feature learning in neural networks (NNs) remains a significant challenge. The work of (Mousavi-Hosseini et al.,

A Grid-Based Framework for E-Scooter Demand Representation and Temporal Input Design for Deep Learning: Evidence from Austin, Texas

arXiv:2603.13609v2 Announce Type: replace Abstract: Despite progress in deep learning for shared micromobility demand prediction, the systematic design and statistical validation of temporal input str

A novel YOLO26-MoE optimized by an LLM agent for insulator fault detection considering UAV images

arXiv:2605.19595v1 Announce Type: cross Abstract: The inspection of electrical power line insulators is essential for ensuring grid reliability and preventing failures caused by damaged or degraded in

agentsarxiv-cs-ai

A Practical Framework of Key Performance Indicators for Multi-Robot Lunar and Planetary Field Tests

arXiv:2601.20529v3 Announce Type: replace Abstract: Robotic prospecting for critical resources on the Moon, such as ilmenite, rare earth elements, and water ice, requires robust exploration methods gi

researcharxiv-cs-ro

Agentic Trading: When LLM Agents Meet Financial Markets

arXiv:2605.19337v1 Announce Type: new Abstract: A growing body of work explores how Large Language Models (LLMs) can be embedded in trading systems as agents that perceive market information, retrieve

agentsarxiv-cs-ai

An Empirical Investigation of Reconstruction-Based Models for Seizure Prediction from ECG Signals

arXiv:2504.08381v2 Announce Type: replace-cross Abstract: Epileptic seizures are transient neurological events characterized by abnormal and excessive neuron activity in the brain, which are often ass

applicationsarxiv-cs-lg

An Objective Performance Evaluation of the LSTM Networks in Time Series Classification

arXiv:2605.19311v1 Announce Type: new Abstract: The rapid adoption of deep learning has increasingly led to data-driven models replacing classical model-based algorithms, even in domains governed by w

AQuaUI: Visual Token Reduction for GUI Agents with Adaptive Quadtrees

arXiv:2605.19260v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have recently emerged as promising backbones for GUI-agent models, where high-resolution GUI screenshots are introduced t

agentsarxiv-cs-ai

AR1-ZO: Topology-Aware Rank-1 Zeroth-Order Queries for High-Rank LoRA Fine-Tuning

arXiv:2605.19767v1 Announce Type: cross Abstract: Zeroth-order (ZO) optimization enables large-language-model fine-tuning without storing backpropagation activations, while LoRA supplies compact train

researcharxiv-cs-ai

Artificial Intelligence, conceptual metaphors and conceptual engineering: Are AI-based framings of human behaviour and cognition successful?

arXiv:2504.07756v2 Announce Type: replace Abstract: Understanding human behaviour, neuroscience and psychology using concepts from the domain of AI is increasing in popularity. Given the massive integ

researcharxiv-cs-ai