Search: “applications”

MIND the Gap: A Geographic Implicit Neural Representation with Adjustable Spatial Scale

arXiv:2609.25454v1 Announce Type: cross Abstract: Geographic measurements are often sparse, leaving large areas without labels for the quantities we want to map. Geographic implicit neural representat

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PROSWIN: Probabilistic Solar Wind Speed Forecasting Using Deep Distributional Regression From Solar Images

DGX agent

arXiv:2609.26683v1 Announce Type: cross Abstract: Accurately predicting fast solar wind conditions is challenging, as uncertainties are large and unquantified by traditional single-value prediction mo

researcharxiv-cs-lg

23 Sept 2026

Semantic-Anchored Evidential Fusion for Domain-Robust Whole-Slide Survival Analysis

arXiv:2606.19966v2 Announce Type: replace-cross Abstract: Whole-slide images (WSIs) are widely used for computational cancer prognosis. However, most existing methods primarily focus on in-domain perf

Semantic Self-Distillation for Language Model Uncertainty

arXiv:2602.04577v3 Announce Type: replace Abstract: Large language models present challenges for principled uncertainty quantification, in part due to their complexity and the diversity of their outpu

researcharxiv-cs-cl

Statistical Rates for Entropic Optimal Transport in the Discrete to SubGaussian Regime

arXiv:2609.26647v1 Announce Type: cross Abstract: We study statistical rates in entropic optimal transport in the semi-discrete regime where one measure has finite support and the other is subGaussian

Towards Adaptive Interaction Strategies for Human Companion Robot via Deep Reinforcement Learning

arXiv:2609.25031v1 Announce Type: new Abstract: In the field of Human-Robot Interaction (HRI), achieving flexibility in human-accompanying within real-world environments holds great potential for vari

Tutorials

You've Seen Enough: Quality-Constrained Image Coding for Machines

arXiv:2609.25108v1 Announce Type: new Abstract: Visual data is increasingly consumed by machine-vision systems rather than by human observers. Image Coding for Machines (ICM) compresses images assumin

tutorialsarxiv-cs-cv

A discrete generative model of neuronal spiking activity on microelectrode arrays

arXiv:2609.23907v1 Announce Type: new Abstract: Generative models of neural activity could help characterize tissue dynamics, compare experimental conditions, and simulate population activity for appl

A Mathematical Framework and a Suite of Learning Techniques for Neural-Symbolic Systems

arXiv:2407.09693v3 Announce Type: replace Abstract: The field of Neural-Symbolic (NeSy) systems is growing rapidly. Proposed approaches show great promise in achieving symbiotic unions of neural and s

safetyarxiv-cs-lg

A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agents

arXiv:2601.12538v2 Announce Type: replace-cross Abstract: Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) de

agentsarxiv-cs-cl

Adaptive Forgetting for Nonstationary Optimization: Towards Robust EEG Decoding

arXiv:2609.24233v1 Announce Type: new Abstract: Electroencephalography (EEG) provides non-invasive monitoring of brain activity and is widely used in emotion recognition, motor imagery and sleep stagi

safetyarxiv-cs-lg

ALPCAHUS: Subspace Clustering for Heteroscedastic Data

arXiv:2505.18918v4 Announce Type: replace-cross Abstract: Principal component analysis (PCA) is a key tool in the field of data dimensionality reduction. Various methods have been proposed to extend P

AquaCap: A Training-Free Underwater Embodied Agent with Code-as-Policy

model-releasesarxiv-cs-ro

arXiv:2609.23133v1 Announce Type: new Abstract: Recent advances in vision-language-action models have stimulated growing interest in underwater embodied intelligence. However, their reliance on large-

Assessing Readability with LLMs: The Role of Reasoning and Few-Shot Prompting

arXiv:2609.24650v1 Announce Type: new Abstract: Readability assessment is essential for tailoring texts to intended audiences across educational, healthcare, and information retrieval domains. However

Augmenting PID Control with Deep Reinforcement Learning: A Hybrid Approach to the Industrial Benchmark

arXiv:2609.22584v1 Announce Type: new Abstract: As industrial processes grow in complexity, traditional Proportional-Integral-Derivative (PID) controllers are often insufficient for handling their non

Barrier Certificate Synthesis for Non-Polynomial Robotic Dynamics via Polynomial Lifting

arXiv:2609.22885v1 Announce Type: new Abstract: Safe operation of robotic systems requires trajectories to remain within a prescribed safe set under admissible control inputs. Barrier certificates pro

Belted Engression: Sufficient Dimension Reduction for Generative Distributional Regression

arXiv:2609.23789v1 Announce Type: new Abstract: Modern conditional generative models face significant challenges when learning complex covariate dependencies. While sufficient dimension reduction (SDR

Beyond Uniform Subspaces: Spectrum-Aware and Depth-Adaptive Fusion for Multi-Task Model Merging

arXiv:2609.24612v1 Announce Type: new Abstract: Model merging aims to consolidate multiple task-specific models without access to extra training process. However, existing subspace-based methods large

researcharxiv-cs-cv

BoundInk: Boundary-Aware Online Handwriting Generation

model-releasesarxiv-cs-cv

arXiv:2604.02103v3 Announce Type: replace Abstract: Realistic online handwriting depends not only on individual character shapes, but also on how a writer connects, spaces, and aligns adjacent charact

Canonical Procedural Actions: An Auditable Annotation Protocol for Tool-Use Agent Traces

arXiv:2609.24264v1 Announce Type: new Abstract: Tool-use agent traces identify messages and API calls, but procedural analyses also need explicit units of action and inspectable links to their evidenc

agentsarxiv-cs-cl

Claude Opus 5.5, GPT-6 Sol, GPT-6 Luna, and a new price war

model-releasessimon-willison

Yesterday was Grok 4.7 (pelicans) and MiMo v2.6 Flash/Pro (more pelicans). Today Anthropic released Claude Opus 5.5, and around an hour later OpenAI released GPT-6 Sol and GPT-6 Luna. It's going to ta

CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey

arXiv:2504.14280v2 Announce Type: replace Abstract: As machine learning evolves, domain generalization (DG) and domain adaptation (DA) have become crucial for improving model robustness across diverse

safetyarxiv-cs-cv

Combining Foundation Model Confidence and Monocular Depth for Training-Free Out-of-Distribution Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.22896v1 Announce Type: new Abstract: Autonomous vehicles operating in open-world scenarios are inevitably confronted with previously unknown objects, such as exotic animals or loose cargo.

Compound-QA: A Benchmark for Evaluating LLMs on Compound Questions

arXiv:2411.10163v3 Announce Type: replace Abstract: Large language models (LLMs) demonstrate remarkable performance across various tasks, prompting researchers to develop diverse evaluation benchmarks

Connect the Dots: Training LLMs for Long-Lifecycle Agents with Cross-Domain Generalization Via Reinforcement Learning

arXiv:2606.20002v2 Announce Type: replace-cross Abstract: This work presents a general framework for training large language models (LLMs) to 'Connect the Dots' (CoD), a meta-capability required by lo

agentsarxiv-cs-cl

Correct-by-Construction Vision-based Pose Estimation using Geometric Generative Models

arXiv:2601.17556v2 Announce Type: replace Abstract: We consider the problem of vision-based pose estimation for autonomous systems. While deep neural networks have been successfully used for vision-ba

CTSpinoPelvic1K: spine, pelvis, ribs and femora in one coordinate frame, annotated for lumbosacral transitional anatomy

arXiv:2609.22760v1 Announce Type: cross Abstract: Purpose: A vertebra at the lumbosacral junction is named by counting caudally from C2 on whole-spine imaging, but a lumbar case is planned on lumbar-o

Design and Control of a Cable-Driven Switchable Actuator with Torque/Tension Dual Modes for Exoskeletons

arXiv:2609.23487v1 Announce Type: new Abstract: Existing wearable exoskeleton architectures are typically constrained by a single mechanical output modality, providing either joint torque around an an

researcharxiv-cs-ro

Didactic knowledge or Clinical Cases? How Data Types Shape Medical Large Language Models

arXiv:2609.22161v1 Announce Type: cross Abstract: Medical large language models are commonly trained on mixtures of didactic data (e.g., textbooks) and clinical data (e.g., patient records), yet how t

researcharxiv-cs-cl

Dimensionality reduction for AI based hyperspectral image classification based on XAI

arXiv:2609.22333v1 Announce Type: new Abstract: This research addresses the challenge of limited material recycling in wood recycling processes by leveraging artificial intelligence (AI)-based dimensi

researcharxiv-cs-cv

Dissecting Training-Free Uncertainty Estimation in Multimodal Large Language Models

arXiv:2609.22206v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable performance across a wide range of multimodal tasks, yet understanding and quantifying

Enhancing Shrimp Disease Detection via Deep Learning and Data Refinement for Resilient Aquaculture

arXiv:2609.23397v1 Announce Type: new Abstract: Shrimp diseases continue to cause devastating losses in the aquaculture industry, driving a critical need for robust, automated detection. This work con

researcharxiv-cs-cv

Enhancing speech representation learning with cross-modal knowledge transfer with HGNN under low resource settings: the case study of Yemba

arXiv:2609.23194v1 Announce Type: new Abstract: Acoustic representation learning is crucial for speech processing, yet low-resource languages (LRLs) face severe data scarcity, limiting the effectivene

Estimation and Control of Tensegrity Manipulator Kinematics based on Strut Inclination Angles

arXiv:2609.24535v1 Announce Type: new Abstract: Unlike conventional rigid-link robots defined by discrete joints, continuum robots pose a fundamental challenge for expressing their complex continuous

researcharxiv-cs-ro

Experimental Evaluation of a Low-Power Ultra-Wideband Receiver for Spectrum Sensing

arXiv:2609.22134v1 Announce Type: cross Abstract: Walsh-sequence-based receiver architectures offer an alternative approach for the reception and reconstruction of multiple simultaneous RF signals ove

Local Ai

FedMust: Semi-supervised Multi-task Student-Teacher Federated Learning for Multi-organ CT Segmentation

arXiv:2609.24627v1 Announce Type: new Abstract: Multi-organ segmentation using deep learning requires large amounts of annotated patient data; however, institutions often lack sufficiently large and d

local-aiarxiv-cs-cv

Financial Language Models as Applied Artificial Intelligence Systems for News-Based Trading under Market Frictions

arXiv:2609.23703v1 Announce Type: new Abstract: Financial language models can transform unstructured firm-specific news into structured decision signals, but financial AI research lacks an integrated

researcharxiv-cs-cl

FinsSim: A Reality-Aligned Integrated Simulation Platform for Underwater Robot Learning

arXiv:2609.23943v1 Announce Type: new Abstract: Underwater robot learning relies on simulators that integrate high-fidelity hydrodynamics, convenient learning interfaces, and a credible transition to

researcharxiv-cs-ro

Hardware

FlashBoB: I/O-Efficient Exact Backward-over-Backward for Softmax Attention

arXiv:2609.24089v1 Announce Type: new Abstract: Transformer models built on the attention mechanism have become a central building block in modern deep learning, yet softmax attention remains a major

hardwarearxiv-cs-lg

Hardware

G6D: Geometric Learning-Free RGB-D 6D Pose Solver for Robotic Manipulation

arXiv:2609.23566v1 Announce Type: new Abstract: 6D object pose estimation is fundamental to robotic manipulation and automation. Recent zero-shot methods have significantly improved generalization to

hardwarearxiv-cs-cv

GeCCo -- a Generalist Contact-Conditioned Policy for Loco-Manipulation Skills on Legged Robots

arXiv:2509.17582v2 Announce Type: replace Abstract: Most modern approaches to quadruped locomotion focus on using Deep Reinforcement Learning (DRL) to learn policies from scratch, in an end-to-end man

General Collaborative Intelligence: Architecting Cognition for Resilient Multi-Agent Ecosystems

model-releasesarxiv-cs-cv

arXiv:2609.22967v1 Announce Type: new Abstract: Multi-agent unmanned systems are moving from isolated, ego-centric sensing toward collaborative intelligence, in which distributed agents exchange compa

Genie One MCP: Give any AI Agent the Right Business Context

**Genie One MCP: Give any AI Agent the Right Business Context** The guide introduces Genie One MCP as a framework for embedding relevant business context in artificial intelligence agents, enabling th

agentsdatabricks

Hierarchical Bayesian optimization of an aircraft-based multi-agent system-of-systems

arXiv:2609.22130v1 Announce Type: new Abstract: Developing innovative system architectures increasingly relies on advanced modeling and optimization techniques to frame the architecting process and de

agentsarxiv-cs-lg

Highly-Efficient Differentiable Simulation for Robotics

model-releasesarxiv-cs-ro

arXiv:2409.07107v3 Announce Type: replace Abstract: Robotics simulators have improved significantly in computational speed and scalability, enabling them to generate years of simulated data for comple

Hybrid Uncertainty Sensitivity Analysis Based on the HSIC for High-Dimensional Responses with Aleatory--Epistemic Separation

arXiv:2606.14053v2 Announce Type: replace-cross Abstract: Quantifying the influence of hybrid aleatory and epistemic uncertainties on high-dimensional system responses remains a major challenge in glo

Improved Private Sparse Covariance Estimation with Multiscale Threshold Tests

arXiv:2609.22783v1 Announce Type: new Abstract: We study differentially private covariance estimation in operator norm for mean-zero sub-Gaussian distributions with unknown covariance support and at m

Information-Directed Sampling for Causal Bandits

arXiv:2607.15577v2 Announce Type: replace Abstract: Causal bandits exploit structural relationships among variables to share information across interventions and accelerate the identification of high-