Search: “framework”

First-Principles AI finds crystallization of fractional quantum Hall liquids

arXiv:2602.03927v2 Announce Type: replace-cross Abstract: When does a fractional quantum Hall (FQH) liquid crystallize? Addressing this question requires a framework that treats fractionalization and

researcharxiv-cs-ai

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GAN-Diff : Coupling Pretrained WGAN-GP Features with Conditional Diffusion U-Nets

DGX agent

arXiv:2608.22272v1 Announce Type: cross Abstract: Generative adversarial networks (GANs) can provide efficient image generation, while diffusion models offer high-quality image restoration but require

model-releasesarxiv-cs-ai

25 Aug 2026

Gaussian process learning with flow map refinement for parameter estimation in dynamical systems

model-releasesarxiv-cs-lg

arXiv:2608.22324v1 Announce Type: new Abstract: Parameter estimation is a central task in data-driven learning of dynamical systems. It aims to recover the underlying physical parameters from observed

Geometric Structures on Graphs: a Holonomy-Based Discretization of Curvature

arXiv:2608.22453v1 Announce Type: new Abstract: We propose a holonomy-based framework for discretizing curvature on graphs equipped with local symmetric positive-definite metrics. Each vertex carries

Agents

GeoWAM: Visual Geometry World Action Models for Autonomous Driving

arXiv:2608.23486v1 Announce Type: new Abstract: World action models (WAMs) have recently gained increasing attention as a framework for jointly modeling scene evolution and ego actions in autonomous d

agentsarxiv-cs-cv

GSAR: Goal-State-Anchor Rewards for Mobile GUI Agents with Self-Evolving Data Synthesis

arXiv:2608.22847v1 Announce Type: new Abstract: Vision-Language Models (VLMs) based GUI agents stand to benefit significantly from online reinforcement learning (RL). However, their training is bottle

iScheduler: Reinforcement Learning-Driven Continual Optimization for Large-Scale Resource Investment Problems

arXiv:2602.06064v2 Announce Type: replace-cross Abstract: Scheduling precedence-constrained tasks under shared renewable resources is critical to modern computing platforms. It is often modeled as the

Long-term User Engagement Optimization through Model-agnostic Downstream Rewards Learning

arXiv:2607.14192v3 Announce Type: replace Abstract: As recommender systems mature in the past few years, their optimization objectives have evolved from a primary focusing on short-term behavioral sig

Machine Learning Assisted Inverse Design of Pixelated mmWave Patch Antennas

arXiv:2608.23469v1 Announce Type: cross Abstract: A machine learning-assisted framework for the inverse design of pixelated millimetre-wave patch antennas targeting the 22--30 GHz band is presented. T

researcharxiv-cs-ai

Mover360: Controllable Object Manipulation in 360{eg} Panoramic Images

model-releasesarxiv-cs-cv

arXiv:2608.23238v1 Announce Type: new Abstract: We present Mover360, a controllable object manipulation framework for 360{eg} images. Unlike perspective images, 360{eg} images in equirectangular proje

Multimodal Prompt Learning with Irregular EHRs for Robust Monitoring of Critical Care Patients

arXiv:2608.21941v1 Announce Type: new Abstract: Accurate assessment of patients in intensive care units (ICUs) is essential for timely clinical intervention and improved patient outcomes. Multimodal e

applicationsarxiv-cs-ai

Hardware

Nvidia and Cisco push the enterprise AI factory into the rack-scale era

The Cisco Secure AI Factory with Nvidia has been extended into the rack-scale era, offering enterprises greater full-stack operational capabilities as a result. Designed to give customers a framework

hardwaresiliconangle

On the Convergence of Single-Loop Stochastic Bilevel Optimization with Approximate Implicit Differentiation

arXiv:2602.23633v2 Announce Type: replace Abstract: Stochastic Bilevel Optimization has emerged as a fundamental framework for meta-learning and hyperparameter optimization. Despite the practical prev

Local Ai

OptiSight: Bridging Semantic Reasoning and Geometric Control for Embodied Navigation

arXiv:2608.23354v1 Announce Type: cross Abstract: Autonomous indoor navigation requires both semantic understanding and precise geometric control. We propose OptiSight, a hybrid framework that combine

local-aiarxiv-cs-cv

Polynomial-Time Mistake-Bounded Language Generation

arXiv:2606.16077v2 Announce Type: replace-cross Abstract: In this paper, we introduce a polynomial-time version of the mistake-bounded language generation (MBLG) framework due to Kleinberg, Peale, and

Private Preview: DigitalOcean Managed Agents Runtime Services

model-releasesdigitalocean

AI agents are helping developers, teams, and businesses do more: writing and executing code, conducting research, and running dynamic workflows across systems. But that ability is often bounded by whe

Tutorials

Progressively Learning Heterogeneous Skills in a Unified Latent Space

arXiv:2608.23258v1 Announce Type: new Abstract: We propose HetSkills, a novel framework designed to progressively learn heterogeneous skills within a unified latent space for physics-based character c

tutorialsarxiv-cs-cv

Q-Learning with Stable Infinite-Dimensional Linear Function Approximation

arXiv:2608.22636v1 Announce Type: new Abstract: Q-learning with linear function approximation can be unstable because an arbitrary approximation architecture need not preserve the Bellman contraction.

safetyarxiv-cs-lg

Reference-free Human-Object Interaction Editing

model-releasesarxiv-cs-cv

arXiv:2503.09130v2 Announce Type: replace-cross Abstract: This paper presents InteractEdit, a novel framework for reference-free Human-Object Interaction (HOI) editing that tackles the challenging tas

Safety-Critical Bilateral Teleoperation for Omnidirectional Aerial Manipulation Using Force-Sensorless Haptic Feedback

arXiv:2608.21735v1 Announce Type: new Abstract: This paper presents a safety-critical bilateral teleoperation framework for omnidirectional aerial manipulators that integrates visual and force-sensorl

safetyarxiv-cs-ro

Scaffold CoT: A CoT dataset built around the failures of small model (>5B Params) free form thinking. Hope its useful to you guys!

model-releasesr-localllama

TL;DR - A ~4M example, ~3B token CoT dataset designed around helping small models think more concisely, accurately and reliably. Hi all! For the past few months I have been working on a dataset design

Signal or Noise? A Benchmark Study of Agent Skills in Web Development

model-releasesarxiv-cs-cl

arXiv:2608.23067v1 Announce Type: new Abstract: Agent Skills are reusable procedural modules that are increasingly injected into coding-agent sessions to encode framework conventions, anti-patterns, a

Sparse Additive Off-Policy Evaluation for Reinforcement Learning with Potentially Limited Number of Trajectories

arXiv:2608.22595v1 Announce Type: cross Abstract: We develop a new framework for flexible, nonlinear, and interpretable off-policy evaluation for infinite-horizon reinforcement learning. To handle lar

safetyarxiv-cs-lg

Agents

Sparse Multi-Stage Expert-Agent Routing for Complex Clinical Reasoning

arXiv:2608.21948v1 Announce Type: new Abstract: Complex clinical reasoning requires models to update diagnostic hypotheses as new evidence emerges and to coordinate different medical specialities unde

agentsarxiv-cs-cv

Agents

Spiking Neural Networks for Continuous Control: Neuromorphic Reinforcement Learning in Conventional Computing

arXiv:2608.22729v1 Announce Type: new Abstract: Reinforcement learning (RL) algorithms have made strides over the past decade applying them to a wide range of problems and control tasks. However, the

agentsarxiv-cs-lg

STAGE: Stateful Translation to Agentic Graph Execution with Policy-Scoped Context and Deterministic Control

arXiv:2608.22538v1 Announce Type: new Abstract: Policy-governed agents must interpret case evidence while following an authorized procedure. We present extsc{Stage}, an executable-graph framework that

StereoDiffuer: Diffusion-based Progressive Geometry Modeling with Saliency Attention Perception for Stereo Matching

arXiv:2608.21710v1 Announce Type: new Abstract: With the advance of deep neural networks, the quality of disparity maps obtained through stereo matching has steadily improved. However, existing stereo

researcharxiv-cs-cv

Structured Learning on Mapper Representations

model-releasesarxiv-cs-lg

arXiv:2608.22044v1 Announce Type: cross Abstract: Modern machine learning (ML) methods are highly effective for prediction tasks, but many commonly used representations reduce complex data to fixed di

Symbolic Neural ODEs: Learning interpretable models from time-series data

arXiv:2608.22112v1 Announce Type: new Abstract: We present a machine learning framework for identifying sparse, interpretable models of dynamical systems directly from time-series data. Our approach p

Two-level domain-decomposition AdaGrad method for scalable training of graph neural networks

arXiv:2608.22575v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have emerged as a powerful framework for learning from graph-structured data. However, their efficient training remains c

AGIDefect-4K: A Richly Annotated Dataset for AI-Generated Image Defect Detection, Localization and Explanation

arXiv:2608.20713v1 Announce Type: new Abstract: Generative AI can now produce highly realistic images, yet current models still exhibit subtle but critical defects that undermine their reliability. Wh

researcharxiv-cs-cv

aiXamine: Unified Black-Box Evaluation of Cross-Dimensional Trade-offs in LLM Safety, Security, and Privacy

arXiv:2608.20554v1 Announce Type: cross Abstract: The critical failure modes in deployed large language models (LLMs) are cross-dimensional: a model can score 99.3 in safety alignment while refusing o

safetyarxiv-cs-lg

Bankruptcy Prediction via Hybrid Resampling and Stacking Ensemble Techniques with Explainable Artificial Intelligence (XAI)-Driven Analysis

arXiv:2608.20343v1 Announce Type: new Abstract: This study develops and evaluates a bankruptcy prediction framework that integrates consensus-based feature selection, hybrid resampling, stacking ensem

Bern2Edge: A Neurosymbolic Compiler for Edge Deployment via Bernstein Polynomial Networks

arXiv:2608.20497v1 Announce Type: new Abstract: Deploying high-accuracy neural networks on resource-constrained edge devices remains challenging, as existing approaches treat training, compression, an

Local Ai

ConceptTS: LLM-Guided Concept Bottlenecks for Interpretable Multivariate Time-Series Forecasting

arXiv:2608.21277v1 Announce Type: new Abstract: State-of-the-art multivariate time-series forecasters can model complex temporal and cross-variable dependencies, yet their opaque representations provi

local-aiarxiv-cs-lg

Demonstration-Guided Humanoid Stand-Up on an Emulated Deformable Surface

arXiv:2608.20852v1 Announce Type: new Abstract: This paper presents a reference-guided reinforcement learning framework to generate stand-up motion for a 29-DOF Unitree G1 humanoid on deformable soft

safetyarxiv-cs-ro

Dynamic Context Scheduling: Learning Beyond the Static Universe

arXiv:2608.20799v1 Announce Type: new Abstract: We study dynamic context scheduling as a training instrument for contextual re- inforcement learning. Rather than treating intra-episode context variati

Enhancing LLMs in Predictive Political QA with Semi-Structured Data

arXiv:2608.21218v1 Announce Type: new Abstract: Predictive political question answering (QA), such as predicting how a political actor will vote, goes beyond factual lookup. External political resourc

applicationsarxiv-cs-ai

Evaluating Skills, Not Just Agents: Agentic Continuous Evaluation of Skills

arXiv:2608.20614v1 Announce Type: new Abstract: Enterprise agent programs are moving from prototypes into production, where reusable skills, tools, and workflow packages must be reviewed with evidence

safetyarxiv-cs-ai

Tutorials

Forecasting with an N-dimensional Langevin Equation and a Neural-Ordinary Differential Equation

arXiv:2405.07359v2 Announce Type: replace Abstract: Accurate prediction of electricity day-ahead prices is essential in competitive electricity markets. Although stationary electricity-price forecasti

tutorialsarxiv-cs-lg

Hidden Axis of Uncertainty: Latent-Posterior Alignment in Graph Neural Networks with Bayesian Output Layers

model-releasesarxiv-cs-lg

arXiv:2608.20758v1 Announce Type: new Abstract: Bayesian Neural Networks (BNNs) with Bayesian output layers provide a principled and tractable framework for quantifying predictive uncertainty, yet the

Identify, Locate, Link: End-to-End Key-Value Extraction from Document Images

model-releasesarxiv-cs-cl

arXiv:2608.20868v1 Announce Type: cross Abstract: Document processing pipelines traditionally cascade optical character recognition (OCR) engines with downstream models for structured information extr

Infinite-dimensional generative diffusions via Doob's h-transform

arXiv:2602.06621v2 Announce Type: replace-cross Abstract: This paper introduces a rigorous framework for defining generative diffusion models in infinite dimensions via Doob's h-transform. Rather than

Keyed Provenance Watermarking with Complementary Lattice-Based Secure Aggregation for Federated Learning

arXiv:2608.20580v1 Announce Type: cross Abstract: Federated learning (FL) is vulnerable to multi-level attacks. However, existing methods address them separately, leaving FL exposed to data leakage, u

applicationsarxiv-cs-lg

MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generation

arXiv:2601.06519v2 Announce Type: replace Abstract: Biomedical retrieval-augmented generation (RAG) can ground LLM answers in medical literature, yet long-form outputs often contain isolated unsupport

safetyarxiv-cs-cl

Nonlinear Model Predictive Control for Trajectory Tracking of Differentially Flat Fixed-Wing Aerial Systems

arXiv:2608.20655v1 Announce Type: new Abstract: Planning and control of fixed-wing Unmanned Aerial Vehicles (UAVs) are challenging due to nonlinear dynamics, aerodynamic limits, and environmental dist

applicationsarxiv-cs-ro

SENTRY: Deterministic, Intelligent Risk Assessment for IT Change Management

arXiv:2608.21203v1 Announce Type: new Abstract: Technology change management in large financial institutions depends on risk assessments that are accurate, consistent, and auditable. In practice, many

applicationsarxiv-cs-ai

Spatially Aware Dictionary-Free Koopman Eigenfunction Identification for Modeling and Control

arXiv:2511.22648v2 Announce Type: replace Abstract: A spatially aware dictionary-free eigenfunction discovery (SADFED) framework is proposed for identification of low-rank Koopman models from data wit