Search: “applications”

Multivariate Gaussian NeRF for Wide Field-of-View Ultrasound Reconstruction

arXiv:2604.24187v1 Announce Type: new Abstract: Wide Field-of-View (WFoV) reconstruction enhances 3D ultrasound imaging by providing valuable anatomical context for segmentation models and visualizati

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Research

Pixel-Translation-Equivariant Quantum Convolutional Neural Networks via Fourier Multiplexers

DGX agent

arXiv:2604.06094v2 Announce Type: replace-cross Abstract: Convolutional neural networks owe much of their success to hard-coding translation equivariance. Quantum convolutional neural networks (QCNNs)

researcharxiv-cs-lg

28 Apr 2026

Swa-bhasha Resource Hub: Romanized Sinhala to Sinhala Transliteration Systems and Data Resources

arXiv:2507.09245v2 Announce Type: replace Abstract: The Swa-bhasha Resource Hub provides a comprehensive collection of data resources and algorithms developed for Romanized Sinhala to Sinhala translit

researcharxiv-cs-cl

Time-Series Forecasting in Safety-Critical Environments: An EU-AI-Act-Compliant Open-Source Package / Zeitreihenprognose in sicherheitskritischen Umgebungen: Ein KI-VO-konformes Open-Source-Paket

arXiv:2604.23859v1 Announce Type: new Abstract: With spotforecast2-safe we present an integrated Compliance-by-Design approach to Python-based point forecasting of time series in safety-critical envir

safetyarxiv-cs-ai

Agents

Towards Lawful Autonomous Driving: Deriving Scenario-Aware Driving Requirements from Traffic Laws and Regulations

arXiv:2604.24562v1 Announce Type: new Abstract: Driving in compliance with traffic laws and regulations is a basic requirement for human drivers, yet autonomous vehicles (AVs) can violate these requir

agentsarxiv-cs-ai

Weakly Supervised Multicenter Nancy Index Scoring in Ulcerative Colitis Using Foundation Models

arXiv:2604.23706v1 Announce Type: new Abstract: Histologic assessment of ulcerative colitis (UC) activity is an important endpoint in clinical trials and routine care, but manual grading with indices

H-Sets: Hessian-Guided Discovery of Set-Level Feature Interactions in Image Classifiers

arXiv:2604.22045v1 Announce Type: cross Abstract: Feature attribution methods explain the predictions of deep neural networks by assigning importance scores to individual input features. However, most

Inter-Stance: A Dyadic Multimodal Corpus for Conversational Stance Analysis

arXiv:2604.22739v1 Announce Type: new Abstract: Social interactions dominate our perceptions of the world and shape our daily behavior by attaching social meaning to acts as simple and spontaneous as

Multi-output Extreme Spatial Model for Complex Aircraft Production Systems

model-releasesarxiv-cs-lg

arXiv:2604.22548v1 Announce Type: cross Abstract: Problem definition: Data-driven models in machine learning have enabled efficient management of production systems. However, a majority of machine lea

NRGS: Neural Regularization for Robust 3D Semantic Gaussian Splatting

arXiv:2604.22439v1 Announce Type: new Abstract: We propose a neural regularization method that refines the noisy 3D semantic field produced by lifting multi-view inconsistent 2D features, in order to

UNIKIE-BENCH: Benchmarking Large Multimodal Models for Key Information Extraction in Visual Documents

model-releasesarxiv-cs-cl

arXiv:2602.07038v2 Announce Type: replace-cross Abstract: Key Information Extraction (KIE) from real-world documents remains challenging due to substantial variations in layout structures, visual qual

Syntheses

Wiki Lint Report — 2026-04-26

linthealth-checkautomated

Automated lint: 44 errors, 10 warnings, 3 info

26 Apr 2026

DMAP: A Distribution Map for Text

arXiv:2602.11871v2 Announce Type: replace Abstract: Large Language Models (LLMs) are a powerful tool for statistical text analysis, with derived sequences of next-token probability distributions offer

researcharxiv-cs-cl

GFlowState: Visualizing the Training of Generative Flow Networks Beyond the Reward

arXiv:2604.21830v1 Announce Type: new Abstract: We present GFlowState, a visual analytics system designed to illuminate the training process of Generative Flow Networks (GFlowNets or GFNs). GFlowNets

safetyarxiv-cs-lg

Low-Rank Adaptation Redux for Large Models

model-releasesarxiv-cs-lg

arXiv:2604.21905v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) has emerged as the de facto standard for parameter-efficient fine-tuning (PEFT) of foundation models, enabling the adaptation

On the algebra of Koopman eigenfunctions and on some of their infinities

arXiv:2604.21825v1 Announce Type: cross Abstract: For continuous-time dynamical systems with reversible trajectories, the nowhere-vanishing eigenfunctions of the Koopman operator of the system form a

Retrofit: Continual Learning with Controlled Forgetting for Binary Security Detection and Analysis

model-releasesarxiv-cs-ai

arXiv:2511.11439v2 Announce Type: replace-cross Abstract: Binary security has increasingly relied on deep learning to reason about malware behavior and program semantics. However, the performance ofte

The CriticalSet problem: Identifying Critical Contributors in Bipartite Dependency Networks

arXiv:2604.21537v1 Announce Type: new Abstract: Identifying critical nodes in complex networks is a fundamental task in graph mining. Yet, methods addressing an all-or-nothing coverage mechanics in a

The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

model-releasesarxiv-cs-ai

arXiv:2604.21312v1 Announce Type: cross Abstract: This paper presents the NTIRE 2026 Remote Sensing Infrared Image Super-Resolution (x4) Challenge, one of the associated challenges of NTIRE 2026. The

Agents

AIE Europe Debrief + Agent Labs Thesis: Unsupervised Learning x Latent Space Crossover Special (2026)

This episode discusses developments in unsupervised learning and latent space technologies presented at AIE Europe 2026, with particular focus on how unsupervised learning techniques intersect with la

agentslatent-space

Hardware

Algorithm and Hardware Co-Design for Efficient Complex-Valued Uncertainty Estimation

arXiv:2604.19993v1 Announce Type: cross Abstract: Complex-Valued Neural Networks (CVNNs) have significant advantages in handling tasks that involve complex numbers. However, existing CVNNs are unable

hardwarearxiv-cs-lg

Confidence-Based Mesh Extraction from 3D Gaussians

arXiv:2603.24725v2 Announce Type: replace Abstract: Recently, 3D Gaussian Splatting (3DGS) greatly accelerated mesh extraction from posed images due to its explicit representation and fast software ra

Do We Need Bigger Models for Science? Task-Aware Retrieval with Small Language Models

arXiv:2604.01965v2 Announce Type: replace-cross Abstract: Scientific knowledge discovery increasingly relies on large language models, yet many existing scholarly assistants depend on proprietary syst

Gauge-Equivariant Graph Neural Networks for Lattice Gauge Theories

arXiv:2604.20797v1 Announce Type: cross Abstract: Local gauge symmetry underlies fundamental interactions and strongly correlated quantum matter, yet existing machine-learning approaches lack a genera

Learning When Not to Decide: A Framework for Overcoming Factual Presumptuousness in AI Adjudication

model-releasesarxiv-cs-ai

arXiv:2604.19895v1 Announce Type: new Abstract: A well-known limitation of AI systems is presumptuousness: the tendency of AI systems to provide confident answers when information may be lacking. This

Separable Pathways for Causal Reasoning: How Architectural Scaffolding Enables Hypothesis-Space Restructuring in LLM Agents

arXiv:2604.20039v1 Announce Type: new Abstract: Causal discovery through experimentation and intervention is fundamental to robust problem solving. It requires not just updating beliefs within a fixed

Sheaf Neural Networks on SPD Manifolds: Second-Order Geometric Representation Learning

arXiv:2604.20308v1 Announce Type: new Abstract: Graph neural networks face two fundamental challenges rooted in the linear structure of Euclidean vector spaces: (1) Current architectures represent geo

Snow Flurries: How UNC6692 Employed Social Engineering to Deploy a Custom Malware Suite

model-releasesgoogle-cloud-ai

Written by: JP Glab, Tufail Ahmed, Josh Kelley, Muhammad Umair Introduction Google Threat Intelligence Group (GTIG) identified a multistage intrusion campaign by a newly tracked threat group, UNC6692,

Task-Stratified Knowledge Scaling Laws for Post-Training Quantized Large Language Models

arXiv:2508.18609v4 Announce Type: replace-cross Abstract: Post-Training Quantization (PTQ) is a critical strategy for efficient Large Language Models (LLMs) deployment. However, existing scaling laws

Text to model via SysML: Automated generation of dynamical system computational models from unstructured natural language text via enhanced System Modeling Language diagrams

arXiv:2507.06803v3 Announce Type: replace-cross Abstract: This paper contributes to speeding up the design and deployment of engineering dynamical systems by proposing a strategy for exploiting domain

Using Learning Theories to Evolve Human-Centered XAI: Future Perspectives and Challenges

arXiv:2604.19788v1 Announce Type: new Abstract: As Artificial Intelligence (AI) systems continue to grow in size and complexity, so does the difficulty of the quest for AI transparency. In a world of

Adversarial Label Invariant Graph Data Augmentations for Out-of-Distribution Generalization

arXiv:2604.08404v2 Announce Type: replace Abstract: Out-of-distribution (OoD) generalization occurs when representation learning encounters a distribution shift. This occurs frequently in practice whe

Agents

PLaMo 2.1-VL Technical Report

arXiv:2604.19324v1 Announce Type: cross Abstract: We introduce PLaMo 2.1-VL, a lightweight Vision Language Model (VLM) for autonomous devices, available in 8B and 2B variants and designed for local an

agentsarxiv-cs-ai

Regression with Large Language Models for Materials and Molecular Property Prediction

model-releasesarxiv-cs-lg

arXiv:2409.06080v2 Announce Type: replace-cross Abstract: We demonstrate the ability of large language models (LLMs) to perform material and molecular property regression tasks, a significant deviatio

Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs

arXiv:2410.03294v4 Announce Type: replace Abstract: This study addresses the deployment challenges of integer-only quantized Transformers on resource-constrained embedded FPGAs (Xilinx Spartan-7 XC7S1

RL-ABC: Reinforcement Learning for Accelerator Beamline Control

arXiv:2604.19146v1 Announce Type: new Abstract: Particle accelerator beamline optimization is a high-dimensional control problem traditionally requiring significant expert intervention. We present RLA

safetyarxiv-cs-lg

SitEmb-v1.5: Improved Context-Aware Dense Retrieval for Semantic Association and Long Story Comprehension

model-releasesarxiv-cs-cl

arXiv:2508.01959v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) over long documents typically involves splitting the text into smaller chunks, which serve as the basic units f

SketchFaceGS: Real-Time Sketch-Driven Face Editing and Generation with Gaussian Splatting

arXiv:2604.19202v1 Announce Type: cross Abstract: 3D Gaussian representations have emerged as a powerful paradigm for digital head modeling, achieving photorealistic quality with real-time rendering.

The new Gemini Enterprise: one platform for agent development, orchestration, and governance

model-releasesgoogle-cloud-ai

The first wave of AI changed how we find information; the next wave is changing how we get work done. Today, we’re enhancing our most powerful AI tools and bringing them together under one roof. Gemin

Local Ai

Towards Auto-Building of Embedded FPGA-based Soft Sensors for Wastewater Flow Estimation

arXiv:2407.05102v2 Announce Type: replace-cross Abstract: Executing flow estimation using Deep Learning (DL)-based soft sensors on resource-limited IoT devices has demonstrated promise in terms of rel

local-aiarxiv-cs-ai

Towards Streaming Target Speaker Extraction via Chunk-wise Interleaved Splicing of Autoregressive Language Model

arXiv:2604.19635v1 Announce Type: cross Abstract: While generative models have set new benchmarks for Target Speaker Extraction (TSE), their inherent reliance on global context precludes deployment in

A Scalable Nystrom-Based Kernel Two-Sample Test with Permutations

arXiv:2502.13570v4 Announce Type: replace-cross Abstract: Two-sample hypothesis testing-determining whether two sets of data are drawn from the same distribution-is a fundamental problem in statistics

Advancing Vision Transformer with Enhanced Spatial Priors

arXiv:2604.18549v1 Announce Type: new Abstract: In recent years, the Vision Transformer (ViT) has garnered significant attention within the computer vision community. However, the core component of Vi

Industry

Announcing our 2026 Google Cloud Partners of the Year

Google Cloud is honored to present the 2026 Partner of the Year winners! These awards recognize partners who have displayed a commitment to excellence by leveraging Google Cloud technology to deliver

industrygoogle-cloud-ai

Attention Is not Everything: Efficient Alternatives for Vision

arXiv:2604.17439v1 Announce Type: new Abstract: Recently computer vision has seen advancements mainly thanks to Transformer-based models. However many non-Transformer methods are still doing well bein

AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction

arXiv:2510.15339v3 Announce Type: replace Abstract: Building effective knowledge graphs (KGs) for Retrieval-Augmented Generation (RAG) is pivotal for advancing question answering (QA) systems. However

safetyarxiv-cs-cl

AvatarPointillist: AutoRegressive 4D Gaussian Avatarization

arXiv:2604.04787v2 Announce Type: replace Abstract: We introduce AvatarPointillist, a novel framework for generating dynamic 4D Gaussian avatars from a single portrait image. At the core of our method

Barrier-enforced multi-objective optimization for direct point and sharp interval forecasting

arXiv:2604.18492v1 Announce Type: new Abstract: This paper proposes a multi-step probabilistic forecasting framework using a single neural-network based model to generate simultaneous point and interv