Search: “applications”

Prediction of Alzheimer's Disease Risk Factors from Retinal Images via Deep Learning: Development and Validation of Biologically Relevant Morphological Associations in the UK Biobank

arXiv:2605.00665v1 Announce Type: new Abstract: The systemic, metabolic, lifestyle factors have established associations with Alzheimer's Disease (AD) through epidemiologic and AD-specific biomarker s

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Robust Fusion of Object-Level V2X for Learned 3D Object Detection

arXiv:2605.00595v1 Announce Type: new Abstract: Perception for automated driving is largely based on onboard environmental sensors, such as cameras and radar, which are cost-effective but limited by l

Scaling Federated Linear Contextual Bandits via Sketching

arXiv:2605.00500v1 Announce Type: new Abstract: In federated contextual linear bandits, high data dimensionality incurs prohibitive computation and communication costs: local agents perform O(d^3)-tim

Stereo Multistage Spatial Attention for Real-Time Mobile Manipulation Under Visual Scale Variation and Disturbances

arXiv:2605.00471v1 Announce Type: new Abstract: Robots operating in open, unstructured real-world environments must rely on onboard visual perception while autonomously moving across different locatio

Structure-Aware Chunking for Tabular Data in Retrieval-Augmented Generation

arXiv:2605.00318v1 Announce Type: new Abstract: Tabular documents such as CSV and Excel files are widely used in enterprise data pipelines, yet existing chunking strategies for retrieval-augmented gen

Surprisal Minimisation over Goal-directed Alternatives Predicts Production Choice in Dialogue

arXiv:2605.00506v1 Announce Type: new Abstract: We model utterance production as probabilistic cost-sensitive choice over contextual alternatives, using information-theoretic notions of cost. We disti

SynQuE: Estimating Synthetic Dataset Quality Without Annotations

arXiv:2511.03928v5 Announce Type: replace Abstract: We introduce and formalize the Synthetic Dataset Quality Estimation (SynQuE) problem: ranking synthetic datasets by their expected real-world task p

Task-Conditioned Uncertainty Costmaps for Legged Locomotion

arXiv:2605.00261v1 Announce Type: new Abstract: Legged robots maintain dynamic feasibility through multicontact interactions with terrain. Learned foothold prediction can provide feasibility-aware cos

TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning

arXiv:2605.00015v1 Announce Type: cross Abstract: Time Series Foundation Models (TSFMs) advance generalization and data efficiency in time series forecasting by unified large-scale pretraining. But TS

Model Releases

Vesselpose: Vessel Graph Reconstruction from Learned Voxel-wise Direction Vectors in 3D Vascular Images

model-releasesarxiv-cs-cv

arXiv:2605.00538v1 Announce Type: new Abstract: Blood vessel segmentation and -tracing are essential tasks in many medical imaging applications. Although numerous methods exist, the prevailing segment

Weisfeiler Lehman Test on Combinatorial Complexes: Generalized Expressive Power of Topological Neural Networks

arXiv:2605.00725v1 Announce Type: new Abstract: Combinatorial complexes have unified set-based (e.g., graphs, hypergraphs) and part-whole (e.g., simplicial, cellular complexes) structures into a commo

A Pattern Language for Resilient Visual Agents

arXiv:2604.28001v1 Announce Type: new Abstract: Integrating multimodal foundation models into enterprise ecosystems presents a fundamental software architecture challenge. Architects must balance comp

A Unified Framework of Hyperbolic Graph Representation Learning Methods

arXiv:2604.28070v1 Announce Type: new Abstract: Hyperbolic geometry has emerged as an effective latent space for representing complex networks, owing to its ability to capture hierarchical organizatio

AI Inference as Relocatable Electricity Demand: A Latency-Constrained Energy-Geography Framework

arXiv:2604.27855v1 Announce Type: cross Abstract: AI inference is becoming a persistent and geographically distributed source of electricity demand. Unlike many traditional electrical loads, inference

Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI

arXiv:2510.04978v5 Announce Type: replace Abstract: The rapid advancement of embodied intelligence and world models has intensified efforts to integrate physical laws into AI systems, yet physical per

Safety

Automatic Causal Fairness Analysis with LLM-Generated Reporting

arXiv:2604.27011v1 Announce Type: cross Abstract: AutoML, intended as the process of automating the application of machine learning to real-world problems, is a key step for AI popularisation. Most Au

safetyarxiv-cs-ai

Hardware

Benchmarking Deep Learning Models for Object Detection on Edge Computing Devices

arXiv:2409.16808v1 Announce Type: cross Abstract: Modern applications, such as autonomous vehicles, require deploying deep learning algorithms on resource-constrained edge devices for real-time image

hardwarearxiv-cs-lg

ConformaDecompose: Explaining Uncertainty via Calibration Localization

arXiv:2604.27149v1 Announce Type: cross Abstract: Conformal Prediction provides distribution-free prediction intervals with guaranteed coverage, but its reliance on a single global calibration thresho

Safety

Consumer Attitudes Towards AI in Digital Health: A Mixed-Methods Survey in Australia

arXiv:2604.27744v1 Announce Type: new Abstract: AI applications are increasingly being introduced into digital health. While technical performance has advanced rapidly, successful deployment mainly de

safetyarxiv-cs-ai

Context as Prior: Bayesian-Inspired Intent Inference for Non-Speaking Agents with a Household Cat Testbed

arXiv:2604.27445v1 Announce Type: new Abstract: Many agents in real-world environments cannot reliably communicate their goals through language, including household pets, pre-verbal infants, and other

Safety

Efficient Preimage Approximation for Neural Network Certification

arXiv:2505.22798v3 Announce Type: replace-cross Abstract: The growing reliance on artificial intelligence in safety- and security-critical applications is raising concerns about the robustness of neur

safetyarxiv-cs-ai

Epistemic reflections on AI answering our questions: overwatch, erudite, logician, interlocutor

arXiv:2304.14352v2 Announce Type: replace-cross Abstract: Currently, there is a trend for the wider public to rely on LLMs for financial or legal consultation, medical and mental support (Chatterji et

ExoActor: Exocentric Video Generation as Generalizable Interactive Humanoid Control

arXiv:2604.27711v1 Announce Type: new Abstract: Humanoid control systems have made significant progress in recent years, yet modeling fluent interaction-rich behavior between a robot, its surrounding

Research

Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models

arXiv:2604.28149v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) have recently emerged as general-purpose forecasting models and show considerable potential for applications in en

researcharxiv-cs-lg

Exploring Vision Neural Network Pruning via Screening Methodology

arXiv:2502.07189v2 Announce Type: replace Abstract: The remarkable performance of modern deep neural networks (DNNs) is largely driven by their massive scale, often comprising tens to hundreds of mill

FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning

arXiv:2604.28024v1 Announce Type: new Abstract: Federated Multi-Label Learning is a distributed paradigm where multiple clients possess heterogeneous multi-label data and perform collaborative learnin

FinCARDS: Card-Based Analyst Reranking for Financial Document Question Answering

arXiv:2601.06992v2 Announce Type: replace-cross Abstract: Financial question answering (QA) over long corporate filings requires evidence to satisfy strict constraints on entities, financial metrics,

From LLM-Driven Trading Card Generation to Procedural Relatedness: A Pokemon Case Study

arXiv:2604.27972v1 Announce Type: new Abstract: Since the dawn of Trading Card Games, the genre has grown into a multi-billion-dollar industry engaging millions of analog and digital players worldwide

From Unstructured to Structured: LLM-Guided Attribute Graphs for Entity Search and Ranking

arXiv:2604.27410v1 Announce Type: cross Abstract: Entity search, i.e., finding the most similar entities to a query entity, faces unique challenges in e-commerce, where product similarity varies acros

GourNet: A CNN-Based Model for Mango Leaf Disease Detection

arXiv:2604.27764v1 Announce Type: new Abstract: Mango cultivation is crucial in the agricultural sector, significantly contributing to economic development and food security. However, diseases affecti

Green Physics-Informed Machine Learning Models For Structural Health Monitoring

arXiv:2604.27638v1 Announce Type: new Abstract: Machine learning continues to emerge as an important tool to be utilised within structural engineering and structural health monitoring, due to its abil

Improving Calibration in Test-Time Prompt Tuning for Vision-Language Models via Data-Free Flatness-Aware Prompt Pretraining

arXiv:2604.27715v1 Announce Type: new Abstract: Test-time prompt tuning (TPT) has emerged as a promising technique for enhancing the adaptability of vision-language models by optimizing textual prompt

Interaction Forces and Internal Loads in Parallel Manipulators with Actuation Redundancy

arXiv:2604.27095v1 Announce Type: new Abstract: This paper discusses null-space wrench components in parallel manipulators. We examine the adaptation of the two most common characterizations of these

JaiTTS: A Thai Voice Cloning Model

arXiv:2604.27607v1 Announce Type: new Abstract: We present JaiTTS-v1.0, a state-of-the-art Thai voice cloning text-to-speech model built through continual training on a large Thai-centric speech corpu

Latent Adversarial Detection: Adaptive Probing of LLM Activations for Multi-Turn Attack Detection

arXiv:2604.28129v1 Announce Type: cross Abstract: Multi-turn prompt injection follows a known attack path -- trust-building, pivoting, escalation but text-level defenses miss covert attacks where indi

Learning to Reason: Targeted Knowledge Discovery and Fuzzy Logic Update for Robust Image Recognition

arXiv:2604.27759v1 Announce Type: cross Abstract: Integrating domain knowledge into deep neural networks is a promising way to improve generalization. Existing methods either encode prior knowledge in

LLM-based User Profile Management for Recommender System

arXiv:2502.14541v3 Announce Type: replace Abstract: The rapid advancement of Large Language Models (LLMs) has opened new opportunities in recommender systems by enabling zero-shot recommendation witho

Making Conformal Predictors Robust in Healthcare Settings: a Case Study on EEG Classification

arXiv:2602.19483v2 Announce Type: replace-cross Abstract: Quantifying uncertainty in clinical predictions is critical for high-stakes diagnosis tasks. Conformal prediction offers a principled approach

Making Logic a First-Class Citizen in Generative ML for Networking

arXiv:2506.23964v3 Announce Type: replace-cross Abstract: Generative ML models are increasingly popular in networking for tasks such as telemetry imputation, prediction, and synthetic trace generation

Mull-Tokens: Modality-Agnostic Latent Thinking

arXiv:2512.10941v2 Announce Type: replace-cross Abstract: Reasoning goes beyond language; the real world requires reasoning about space, time, affordances, and much more that words alone cannot convey

Optimized Deferral for Imbalanced Settings

arXiv:2604.27723v1 Announce Type: new Abstract: Learning algorithms can be significantly improved by routing complex or uncertain inputs to specialized experts, balancing accuracy with computational c

Position-Aware Drafting for Inference Acceleration in LLM-Based Generative List-Wise Recommendation

arXiv:2604.27747v1 Announce Type: cross Abstract: Large language model (LLM)-based generative list-wise recommendation has advanced rapidly, but decoding remains sequential and thus latency-prone. To

Predicting Covariate-Driven Spatial Deformation for Nonstationary Gaussian Processes

arXiv:2604.27280v1 Announce Type: new Abstract: Nonstationary Gaussian processes (GPs) are essential for modeling complex, locally heterogeneous spatial data. A common modeling approach is the spatial

Probabilistic Circuits for Irregular Multivariate Time Series Forecasting

arXiv:2604.27814v1 Announce Type: new Abstract: Joint probabilistic modeling is essential for forecasting irregular multivariate time series (IMTS) to accurately quantify uncertainty. Existing approac

Profiles of AI Dependency: A Latent Class Analysis of Filipino Students' Academic Competencies

arXiv:2604.27349v1 Announce Type: cross Abstract: The increasing dependency among Filipino college students on artificial intelligence (AI) poses concerns about the potential decline of fundamental ac

PRTS: A Primitive Reasoning and Tasking System via Contrastive Representations

arXiv:2604.27472v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models advance robotic control via strong visual-linguistic priors. However, existing VLAs predominantly frame pretraining

RayFormer: Modeling Inter- and Intra-Ray Similarity for NeRF-Based Video Snapshot Compressive Imaging

arXiv:2604.27702v1 Announce Type: new Abstract: Video snapshot compressive imaging (SCI) enables the reconstruction of dynamic scenes from a single snapshot measurement. Recently, NeRF-based methods h

Reconstruction by Generation: 3D Multi-Object Scene Reconstruction from Sparse Observations

arXiv:2604.27106v1 Announce Type: cross Abstract: Accurately reconstructing complex full multi-object scenes from sparse observations remains a core challenge in computer vision and a key step toward