Search: “applications”

SAND: The Challenge on Speech Analysis for Neurodegenerative Disease Assessment

arXiv:2604.16445v1 Announce Type: cross Abstract: Recent advances in Artificial Intelligence (AI) and the exploration of noninvasive, objective biomarkers, such as speech signals, have encouraged the

21 Apr 2026

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Research

Score-Based Matching with Target Guidance for Cryo-EM Denoising

DGX agent

arXiv:2604.17734v1 Announce Type: new Abstract: Cryo-electron microscopy (cryo-EM) enables single-particle analysis of biological macromolecules under strict low-dose imaging conditions, but the resul

researcharxiv-cs-cv

21 Apr 2026

SparrowSNN: A Hardware/software Co-design for Energy Efficient ECG Classification

arXiv:2406.06543v2 Announce Type: replace-cross Abstract: Deep learning has driven significant technological advancements, but its high energy consumption limits its use on battery-operated edge devic

21 Apr 2026

Information-Consistent Language Model Recommendations through Group Relative Policy Optimization

arXiv:2512.12858v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in business-critical domains such as finance, education, healthcare, and customer suppo

safetyarxiv-cs-ai

Modeling Parkinson's Disease Progression Using Longitudinal Voice Biomarkers: A Comparative Study of Statistical and Neural Mixed-Effects Models

arXiv:2507.20058v3 Announce Type: replace-cross Abstract: Predicting Parkinson's Disease (PD) progression is crucial for personalized treatment, and voice biomarkers offer a promising non-invasive met

QuantSightBench: Evaluating LLM Quantitative Forecasting with Prediction Intervals

model-releasesarxiv-cs-ai

arXiv:2604.15859v1 Announce Type: cross Abstract: Forecasting has become a natural benchmark for reasoning under uncertainty. Yet existing evaluations of large language models remain limited to judgme

Resource-efficient equivariant quantum convolutional neural networks

arXiv:2410.01252v2 Announce Type: replace-cross Abstract: Equivariant quantum neural networks (QNNs) are promising variational models that exploit symmetries to improve machine learning capabilities.

Splats in Splats++: Robust and Generalizable 3D Gaussian Splatting Steganography

arXiv:2604.15862v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has recently redefined the paradigm of 3D reconstruction, striking an unprecedented balance between visual fidelity and com

TabularMath: Understanding Math Reasoning over Tables with Large Language Models

model-releasesarxiv-cs-ai

arXiv:2505.19563v4 Announce Type: replace Abstract: Mathematical reasoning has long been a key benchmark for evaluating large language models. Although substantial progress has been made on math word

Univariate Channel Fusion for Multivariate Time Series Classification

arXiv:2604.16119v1 Announce Type: new Abstract: Multivariate time series classification (MTSC) plays a crucial role in various domains, including biomedical signal analysis and motion monitoring. Howe

Local Ai

Atropos: Improving Cost-Benefit Trade-off of LLM-based Agents under Self-Consistency with Early Termination and Model Hotswap

arXiv:2604.15075v1 Announce Type: cross Abstract: Open-weight Small Language Models(SLMs) can provide faster local inference at lower financial cost, but may not achieve the same performance level as

local-aiarxiv-cs-lg

Continuous-time reinforcement learning: ellipticity enables model-free value function approximation

arXiv:2602.06930v2 Announce Type: replace Abstract: We study off-policy reinforcement learning for controlling continuous-time Markov diffusion processes with discrete-time observations and actions. W

safetyarxiv-cs-lg

HAMSA: Scanning-Free Vision State Space Models via SpectralPulseNet

arXiv:2604.14724v1 Announce Type: new Abstract: Vision State Space Models (SSMs) like Vim, VMamba, and SiMBA rely on complex scanning strategies to adapt sequential SSMs to process 2D images, introduc

Improved Multiscale Structural Mapping with Supervertex Vision Transformer for the Detection of Alzheimer's Disease Neurodegeneration

arXiv:2604.14837v1 Announce Type: new Abstract: Alzheimer's disease (AD) confirmation often relies on positron emission tomography (PET) or cerebrospinal fluid (CSF) analysis, which are costly and inv

MCPThreatHive: Automated Threat Intelligence for Model Context Protocol Ecosystems

arXiv:2604.13849v1 Announce Type: cross Abstract: The rapid proliferation of Model Context Protocol (MCP)-based agentic systems has introduced a new category of security threats that existing framewor

agentsarxiv-cs-ai

Q-MambaIR: Accurate Quantized Mamba for Efficient Image Restoration

arXiv:2503.21970v3 Announce Type: replace Abstract: State-Space Models (SSMs) have attracted considerable attention in Image Restoration (IR) due to their ability to scale linearly sequence length whi

Quantitative Approximation Rates for Group Equivariant Learning

arXiv:2602.20370v2 Announce Type: replace Abstract: The universal approximation theorem establishes that neural networks can approximate any continuous function on a compact set. Later works in approx

S2AM3D: Scale-controllable Part Segmentation of 3D Point Cloud

arXiv:2512.00995v3 Announce Type: replace Abstract: Part-level point cloud segmentation has recently attracted significant attention in 3D computer vision. Nevertheless, existing research is constrain

A closer look at how large language models trust humans: patterns and biases

arXiv:2504.15801v2 Announce Type: replace Abstract: As large language models (LLMs) and LLM-based agents increasingly interact with humans in decision-making contexts, understanding the trust dynamics

researcharxiv-cs-cl

A Resource-Efficient Hybrid CNN-LSTM network for image-based bean leaf disease classification

arXiv:2604.13835v1 Announce Type: new Abstract: Accurate and resource-efficient automated diagnosis is a cornerstone of modern agricultural expert systems. While Convolutional Neural Networks (CNNs) h

A transformable slender microrobot inspired by nematode parasites for interventional endovascular surgery

arXiv:2604.13513v1 Announce Type: new Abstract: Cardiovascular diseases account for around 17.9 million deaths per year globally, the treatment of which is challenging considering the confined space a

researcharxiv-cs-ro

Adaptive Conformal Prediction for Improving Factuality of Generations by Large Language Models

arXiv:2604.13991v1 Announce Type: new Abstract: Large language models (LLMs) are prone to generating factually incorrect outputs. Recent work has applied conformal prediction to provide uncertainty es

researcharxiv-cs-cl

Can Cross-Layer Transcoders Replace Vision Transformer Activations? An Interpretable Perspective on Vision

arXiv:2604.13304v1 Announce Type: new Abstract: Understanding the internal activations of Vision Transformers (ViTs) is critical for building interpretable and trustworthy models. While Sparse Autoenc

Dehaze-then-Splat: Generative Dehazing with Physics-Informed 3D Gaussian Splatting for Smoke-Free Novel View Synthesis

arXiv:2604.13589v1 Announce Type: new Abstract: We present Dehaze-then-Splat, a two-stage pipeline for multi-view smoke removal and novel view synthesis developed for Track~2 of the NTIRE 2026 3D Rest

DiT as Real-Time Rerenderer: Streaming Video Stylization with Autoregressive Diffusion Transformer

arXiv:2604.13509v1 Announce Type: new Abstract: Recent advances in video generation models has significantly accelerated video generation and related downstream tasks. Among these, video stylization h

Hybrid Approach for Enhancing Lesion Segmentation in Fundus Images

arXiv:2509.25549v2 Announce Type: replace Abstract: Choroidal nevi are common benign pigmented lesions in the eye, with a small risk of transforming into melanoma. Early detection is critical to impro

Learning-Based Estimation of Spatially Resolved Scatter Radiation Fields in Interventional Radiology

arXiv:2512.17654v3 Announce Type: replace Abstract: We present three variants of a lightweight, fully connected artificial neural network, suited for interactive estimation of three-dimensional, spati

LEO-RobotAgent: A General-purpose Robotic Agent for Language-driven Embodied Operator

arXiv:2512.10605v2 Announce Type: replace Abstract: We propose LEO-RobotAgent, a general-purpose language-driven intelligent agent framework for robots. Under this framework, LLMs can operate differen

agentsarxiv-cs-ro

Hardware

MaMe & MaRe: Matrix-Based Token Merging and Restoration for Efficient Visual Perception and Synthesis

arXiv:2604.13432v1 Announce Type: new Abstract: Token compression is crucial for mitigating the quadratic complexity of self-attention mechanisms in Vision Transformers (ViTs), which often involve num

hardwarearxiv-cs-cv

Mobius transforms and Shapley values for vector-valued functions on weighted directed acyclic multigraphs

arXiv:2510.05786v3 Announce Type: replace-cross Abstract: Mobius inversion and Shapley values are two mathematical tools for characterizing and decomposing higher-order structure in complex systems. T

Native Hybrid Attention for Efficient Sequence Modeling

arXiv:2510.07019v3 Announce Type: replace Abstract: Transformers excel at sequence modeling but face quadratic complexity, while linear attention offers improved efficiency but often compromises recal

researcharxiv-cs-cl

On the Fundamental Limitations of Dual Static CVaR Decompositions in Markov Decision Processes

arXiv:2507.14005v2 Announce Type: replace Abstract: It was recently shown that dynamic programming (DP) methods for finding static CVaR-optimal policies in Markov Decision Processes (MDPs) can fail wh

safetyarxiv-cs-lg

Restless Bandits with Individual Penalty Constraints: A New Near-Optimal Index Policy and How to Learn It

arXiv:2604.04101v2 Announce Type: replace Abstract: This paper investigates the Restless Multi-Armed Bandit (RMAB) framework under individual penalty constraints to address resource allocation challen

safetyarxiv-cs-lg

Hardware

Scalable Spatiotemporal Inference with Biased Scan Attention Transformer Neural Processes

arXiv:2506.09163v2 Announce Type: replace Abstract: Neural Processes (NPs) are a rapidly evolving class of models designed to directly model the posterior predictive distribution of stochastic process

hardwarearxiv-cs-lg

Beyond Majority Voting: Efficient Best-Of-N with Radial Consensus Score

arXiv:2604.12196v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challengin

agentsarxiv-cs-cl

Beyond Prompt: Fine-grained Simulation of Cognitively Impaired Standardized Patients via Stochastic Steering

arXiv:2604.12210v1 Announce Type: new Abstract: Simulating Standardized Patients with cognitive impairment offers a scalable and ethical solution for clinical training. However, existing methods rely

Can AI Detect Life? Lessons from Artificial Life

arXiv:2604.11915v1 Announce Type: cross Abstract: Modern machine learning methods have been proposed to detect life in extraterrestrial samples, drawing on their ability to distinguish biotic from abi

DAV-GSWT: Diffusion-Active-View Sampling for Data-Efficient Gaussian Splatting Wang Tiles

arXiv:2602.15355v3 Announce Type: replace Abstract: The emergence of 3D Gaussian Splatting has fundamentally redefined the capabilities of photorealistic neural rendering by enabling high-throughput s

Efficiency of Proportional Mechanisms in Online Auto-Bidding Advertising

arXiv:2604.12799v1 Announce Type: cross Abstract: The rise of automated bidding strategies in online advertising presents new challenges in designing and analyzing efficient auction mechanisms. In thi

El Agente Quntur: A research collaborator agent for quantum chemistry

arXiv:2602.04850v2 Announce Type: replace-cross Abstract: Quantum chemistry is a foundational enabling tool for the fields of chemistry, materials science, computational biology and others. Despite of

agentsarxiv-cs-ai

Hardware

Fine-Tuning LLMs for Report Summarization: Analysis on Supervised and Unsupervised Data

arXiv:2503.10676v2 Announce Type: replace-cross Abstract: We study the efficacy of fine-tuning Large Language Models (LLMs) for the specific task of report (government archives, news, intelligence rep

hardwarearxiv-cs-ai

Information-Theoretic Optimization for Task-Adapted Compressed Sensing Magnetic Resonance Imaging

arXiv:2604.12709v1 Announce Type: cross Abstract: Task-adapted compressed sensing magnetic resonance imaging (CS-MRI) is emerging to address the specific demands of downstream clinical tasks with sign

Machine Learning-Based Real-Time Detection of Compensatory Trunk Movements Using Trunk-Wrist Inertial Measurement Units

arXiv:2604.12591v1 Announce Type: new Abstract: Compensatory trunk movements (CTMs) are commonly observed after stroke and can lead to maladaptive movement patterns, limiting targeted training of affe

researcharxiv-cs-ro

On the continuum limit of t-SNE for data visualization

model-releasesarxiv-cs-lg

arXiv:2604.12041v1 Announce Type: cross Abstract: This work is concerned with the continuum limit of a graph-based data visualization technique called the t-Distributed Stochastic Neighbor Embedding (

One View Is Enough! Monocular Training for In-the-Wild Novel View Generation

arXiv:2603.23488v2 Announce Type: replace Abstract: Monocular novel-view synthesis has long required multi-view image pairs for supervision, limiting training data scale and diversity. We argue it is

PolicyLLM: Towards Excellent Comprehension of Public Policy for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.12995v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly integrated into real-world decision-making, including in the domain of public policy. Yet, their ability t

A Compact and Efficient 1.251 Million Parameter Machine Learning CNN Model PD36-C for Plant Disease Detection: A Case Study

model-releasesarxiv-cs-ai

arXiv:2604.11332v1 Announce Type: cross Abstract: Deep learning has markedly advanced image based plant disease diagnosis as improved hardware and dataset quality have enabled increasingly accurate ne

14 Apr 2026

A Dual Cross-Attention Graph Learning Framework For Multimodal MRI-Based Major Depressive Disorder Detection

arXiv:2604.10116v1 Announce Type: cross Abstract: Major depressive disorder (MDD) is a prevalent mental disorder associated with complex neurobiological changes that cannot be fully captured using a s