Search: “applications”

X-Imitator: Spatial-Aware Imitation Learning via Bidirectional Action-Pose Interaction

arXiv:2605.12162v1 Announce Type: new Abstract: Effectively handling the interplay between spatial perception and action generation remains a critical bottleneck in robotic manipulation. Existing meth

13 May 2026

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Applications

A Breast Vision Pathology Foundation Model for Real-world Clinical Utility

DGX agent

arXiv:2605.08207v1 Announce Type: new Abstract: Pathology foundation models have shown strong retrospective performance, but whether such systems can support clinically relevant use remains unclear. T

applicationsarxiv-cs-cv

12 May 2026

A Cold Diffusion Approach for Percussive Dereverberation

arXiv:2605.10256v1 Announce Type: cross Abstract: Most recent advances in audio dereverberation focus almost exclusively on speech, leaving percussive and drum signals largely unexplored despite their

A Comparative Study of Machine Learning and Deep Learning for Out-of-Distribution Detection

arXiv:2605.10181v1 Announce Type: cross Abstract: Out-of-distribution (OOD) detection is essential for building reliable AI systems, as models that produce outputs for invalid inputs cannot be trusted

A Radius of Robust Feasibility Approach to Directional Sensors in Uncertain Terrain

arXiv:2510.19407v2 Announce Type: replace-cross Abstract: A sensor has the ability to probe its surroundings. However, uncertainties in its exact location can significantly compromise its sensing perf

A Real-Calibrated Synthetic-First Data Engine

arXiv:2605.09699v1 Announce Type: cross Abstract: Modern computer vision systems increasingly encounter performance limitations in data-scarce domains, where collecting large-scale, high-quality label

A Recursive Decomposition Framework for Causal Structure Learning in the Presence of Latent Variables

arXiv:2605.10651v1 Announce Type: cross Abstract: Constraint-based causal discovery is widely used for learning causal structures, but heavy reliance on conditional independence (CI) testing makes it

A Simulated Federated Analysis of MS-Induced Brain Lesions

arXiv:2605.08223v1 Announce Type: new Abstract: Federated techniques such as federated learning and federated analysis have emerged as a powerful paradigm for enabling multi-center research on sensiti

Research

A Tale of Two Problems: Multi-Task Bilevel Learning Meets Equality Constrained Multi-Objective Optimization

arXiv:2605.09094v1 Announce Type: new Abstract: In recent years, bilevel optimization (BLO) has attracted significant attention for its broad applications in machine learning. However, most existing w

researcharxiv-cs-lg

Absurd World: A Simple Yet Powerful Method to Absurdify the Real-world for Probing LLM Reasoning Capabilities

arXiv:2605.09678v1 Announce Type: new Abstract: While extremely powerful and versatile at various tasks, the thinking capabilities of large language models (LLMs) are often put under scrutiny as they

Active Multiple-Prediction-Powered Inference

arXiv:2605.08429v1 Announce Type: cross Abstract: Post-deployment monitoring of healthcare AI requires statistically valid, label-efficient methods, but gold-standard labels from clinician chart revie

Adaptive digital twins for predictive decision-making: Online Bayesian learning of transition dynamics

arXiv:2512.13919v2 Announce Type: replace Abstract: This work shows how adaptivity can enhance value realization of digital twins in civil engineering. We focus on adapting the state transition models

AI Native Asset Intelligence

arXiv:2605.09115v1 Announce Type: cross Abstract: Modern security environments generate fragmented signals across cloud resources, identities, configurations, and third-party security tools. Although

An Integrative Genome-Scale Metabolic Modeling and Machine Learning Framework for Predicting and Optimizing Single-Cell Protein Production in Saccharomyces cerevisiae

arXiv:2603.25561v2 Announce Type: replace Abstract: Saccharomyces cerevisiae is increasingly recognised as a key source for single-cell protein (SCP) production, a rising solution to global protein-su

Behavior-Centric Extraction of Scenarios from Highway Traffic Data and their Domain-Knowledge-Guided Clustering using CVQ-VAE

arXiv:2603.16964v2 Announce Type: replace Abstract: Approval of ADS depends on evaluating its behavior within representative real-world traffic scenarios. A common way to obtain such scenarios is to e

Beyond Accuracy: Evaluating Posterior Fidelity of Diffusion Inverse Solvers

arXiv:2602.04189v2 Announce Type: replace Abstract: Uncertainty evaluation is critical in scientific and engineering inverse problems. However, existing benchmarks on Diffusion Inverse Solvers (DIS) p

Biosignal Fingerprinting: A Cross-Modal PPG-ECG Foundation Model

arXiv:2605.09579v1 Announce Type: cross Abstract: Cardiovascular disease remains the leading cause of global mortality, yet scalable cardiac monitoring is hindered by the gap between diagnostic-rich E

Safety

BONSAI: Bayesian Optimization with Natural Simplicity and Interpretability

arXiv:2602.07144v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) is a popular technique for sample-efficient optimization of black-box functions. In many applications, the paramete

safetyarxiv-cs-ai

Can We Formally Verify Neural PDE Surrogates? SMT Compilation of Small Fourier Neural Operators

arXiv:2605.08938v1 Announce Type: new Abstract: Fourier Neural Operators (FNOs) can greatly accelerate PDE simulation, but they are often used without formal guarantees that they preserve basic physic

CASISR: Circular Arbitrary-Scale Image Super-Resolution

arXiv:2605.08173v1 Announce Type: new Abstract: The generalization performance (GP) of deep learning-based arbitrary-scale image super-resolution (ASISR) methods is subject to limited training dataset

Causal Discovery for Irregularly Time Series with Consistency Guarantees

arXiv:2507.03310v2 Announce Type: replace-cross Abstract: This paper studies causal discovery in irregularly sampled time series-a key challenge in risk-sensitive domains like finance, healthcare, and

Causal Discovery Should Embrace the Wisdom of the Crowd

arXiv:2603.02678v3 Announce Type: replace Abstract: This paper argues for recognizing an emerging paradigm of causal learning by wisdom of the crowd. Recent developments in government, industry, and r

CoDCL: Counterfactual-Inspired Augmentation Contrastive Learning for Temporal Link Prediction in Social Networks

arXiv:2601.22427v2 Announce Type: replace-cross Abstract: Temporal link prediction is crucial for rapidly growing social networks. Existing methods often overlook the underlying causal mechanisms that

Complete Evidence Extraction with Model Ensembles: A Case Study on Medical Coding

arXiv:2511.07055v3 Announce Type: replace Abstract: High-stakes decisions informed by decision support systems require explicit evidence. While prior work focuses on short sufficient evidence, regulat

applicationsarxiv-cs-cl

Conditional anomaly detection methods for patient-management alert systems

arXiv:2605.10847v1 Announce Type: new Abstract: Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection f

Continuum Robot Localization using Distributed Time-of-Flight Sensors

arXiv:2602.07209v2 Announce Type: replace Abstract: Localization and mapping of an environment are crucial tasks for any robot operating in unstructured environments. Time-of-flight (ToF) sensors (e.g

Count Anything at Any Granularity

arXiv:2605.10887v1 Announce Type: new Abstract: Open-world object counting remains brittle: despite rapid advances in vision-language models (VLMs), reliably counting the objects a user intends is far

Counterfactual Stress Testing for Image Classification Models

arXiv:2605.10894v1 Announce Type: new Abstract: Deep learning models in medical imaging often fail when deployed in new clinical environments due to distribution shifts in demographics, scanner hardwa

DANCE: Detect and Classify Events in EEG

arXiv:2605.10688v1 Announce Type: new Abstract: Event identification in continuous neural recordings is a critical task in neuroscience. Decoding in EEG is dominated by classifying windows aligned to

Data-Asymmetric Latent Imagination and Reranking for 3D Robotic Imitation Learning

arXiv:2605.10166v1 Announce Type: new Abstract: Robotic imitation learning typically assumes access to optimal demonstrations, yet real-world data collection often yields suboptimal, exploratory, or e

Debiased Front-Door Learners for Heterogeneous Effects

arXiv:2509.22531v2 Announce Type: replace-cross Abstract: In observational settings where treatment and outcome share unmeasured confounders but an observed mediator remains unconfounded, the front-do

Differentially Private Spectral Graph Clustering: Balancing Privacy, Accuracy, and Efficiency

arXiv:2510.07136v2 Announce Type: replace-cross Abstract: We study spectral graph clustering under edge differential privacy. We propose a matrix shuffling mechanism that combines randomized edge flip

Distilling 3D Spatial Reasoning into a Lightweight Vision-Language Model with CoT

arXiv:2605.09719v1 Announce Type: cross Abstract: Large-scale 3D vision-language models (VLMs) like LLaVA-3D offer strong spatial reasoning but are difficult to deploy due to high computational costs.

Research

Dsat: A Native SAT Solver for Discrete Logic

arXiv:2605.09347v1 Announce Type: new Abstract: Discrete variables are common in many applications, such as probabilistic reasoning, planning and explainable AI. When symbolic reasoning techniques are

researcharxiv-cs-ai

Dynamic Cross-Modal Prompt Generation for Multimodal Continual Instruction Tuning

arXiv:2605.10765v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) achieve strong performance through instruction tuning, yet real-world deployment often requires continual cap

EchoFake: A Replay-Aware Dataset for Practical Speech Deepfake Detection

arXiv:2510.19414v2 Announce Type: replace-cross Abstract: The growing prevalence of speech deepfakes has raised serious concerns, particularly in real-world scenarios such as telephone fraud and ident

Efficient Prompt Learning for Traffic Forecasting

arXiv:2605.08273v1 Announce Type: cross Abstract: Accurate traffic prediction is essential for optimizing transportation systems, enhancing resource allocation, and improving overall urban administrat

Elastic MoE: Unlocking the Inference-Time Scalability of Mixture-of-Experts

arXiv:2509.21892v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models typically fix the number of activated experts k at both training and inference. However, real-world deployment

Elite Polarization in European Parliamentary Speeches: a Novel Measurement Approach Using Large Language Models

arXiv:2507.06658v2 Announce Type: replace-cross Abstract: Theories of democratic stability, populism, and party-system crisis often point to a form of polarization that comparative research rarely mea

Research

Empirical Bayes 1-bit matrix completion

arXiv:2605.09509v1 Announce Type: cross Abstract: The problem of predicting unobserved entries in a binary matrix, known as 1-bit matrix completion, has found diverse applications in fields such as re

researcharxiv-cs-lg

enclawed: A Configurable, Sector-Neutral Hardening Framework for Single-User AI Assistant Gateways

arXiv:2604.16838v2 Announce Type: replace-cross Abstract: We present enclawed, a hard-fork hardening framework built on the OpenClaw AI assistant gateway. enclawed targets deployments that need attest

Equivariant Volumetric Grasping

arXiv:2507.18847v3 Announce Type: replace-cross Abstract: We propose a new volumetric grasp model that is equivariant to rotations around the vertical axis, leading to a significant improvement in sam

ERASE: Eliminating Redundant Visual Tokens via Adaptive Two-Stage Token Pruning

arXiv:2605.09982v1 Announce Type: new Abstract: Recent advancements in Vision-Language Models (VLMs) enable large language models (LLMs) to process high-resolution images, significantly improving real

Establishing Robust Retinal Eye Tracking: A Weakly Supervised Algorithmic Framework

arXiv:2605.09181v1 Announce Type: new Abstract: Retinal image-based eye tracking is widely used in ophthalmic imaging and vision science, and is a promising path to deliver higher gaze accuracy than t

EventTSF: Event-Aware Non-Stationary Time Series Forecasting

arXiv:2508.13434v2 Announce Type: replace-cross Abstract: Time series forecasting is vital in diverse sectors such as energy and transportation, where non-stationary dynamics are deeply intertwined wi

Local Ai

Explainability of Recurrent Neural Networks for Enhancing P300-based Brain-Computer Interfaces

arXiv:2605.10121v1 Announce Type: cross Abstract: Brain-Computer Interfaces (BCIs) based on P300 event-related potentials offer promising applications in health, education, and assistive technologies.

local-aiarxiv-cs-ai

Explainable Machine Learning Framework for Cardiovascular Disease Diagnosis and Prognosis

arXiv:2507.11185v2 Announce Type: replace-cross Abstract: Heart disease continues to pose a critical worldwide health issue, more specifically in areas with insufficient access to healthcare infrastru

Feature Augmentation of GNNs for ILPs: Local Uniqueness Suffices

arXiv:2509.21000v2 Announce Type: replace Abstract: Integer Linear Programs (ILPs) are central to real-world optimizations but notoriously difficult to solve. Learning to Optimize (L2O) has emerged as