Search: “models”

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

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Local Ai

Explainable Fall Detection for Elderly Care via Temporally Stable SHAP in Skeleton-Based Human Activity Recognition

DGX agent

arXiv:2604.13279v1 Announce Type: new Abstract: Fall detection in elderly care requires not only accurate classification but also reliable explanations that clinicians can trust. However, existing pos

local-aiarxiv-cs-cv

16 Apr 2026

Failure Identification in Imitation Learning Via Statistical and Semantic Filtering

arXiv:2604.13788v1 Announce Type: cross Abstract: Imitation learning (IL) policies in robotics deliver strong performance in controlled settings but remain brittle in real-world deployments: rare even

First-See-Then-Design: A Multi-Stakeholder View for Optimal Performance-Fairness Trade-Offs

arXiv:2604.14035v1 Announce Type: new Abstract: Fairness in algorithmic decision-making is often defined in the predictive space, where predictive performance - used as a proxy for decision-maker (DM)

safetyarxiv-cs-lg

Hardware

Fluids You Can Trust: Property-Preserving Operator Learning for Incompressible Flows

arXiv:2602.15472v4 Announce Type: replace-cross Abstract: We present a novel property-preserving kernel-based operator learning method for incompressible flows governed by the incompressible Navier--S

hardwarearxiv-cs-lg

From Order to Distribution: A Spectral Characterization of Forgetting in Continual Learning

arXiv:2604.13460v1 Announce Type: new Abstract: A central challenge in continual learning is forgetting, the loss of performance on previously learned tasks induced by sequential adaptation to new one

Local Ai

GeoLink: A 3D-Aware Framework Towards Better Generalization in Cross-View Geo-Localization

arXiv:2604.13183v1 Announce Type: new Abstract: Generalizable cross-view geo-localization aims to match the same location across views in unseen regions and conditions without GPS supervision. Its cor

local-aiarxiv-cs-cv

Geometric Context Transformer for Streaming 3D Reconstruction

arXiv:2604.14141v1 Announce Type: new Abstract: Streaming 3D reconstruction aims to recover 3D information, such as camera poses and point clouds, from a video stream, which necessitates geometric acc

Goal2Skill: Long-Horizon Manipulation with Adaptive Planning and Reflection

arXiv:2604.13942v1 Announce Type: new Abstract: Recent vision-language-action (VLA) systems have demonstrated strong capabilities in embodied manipulation. However, most existing VLA policies rely on

agentsarxiv-cs-ro

Graph In-Context Operator Networks for Generalizable Spatiotemporal Prediction

arXiv:2603.12725v3 Announce Type: replace Abstract: In-context operator learning enables neural networks to infer solution operators from contextual examples without weight updates. While prior work h

applicationsarxiv-cs-lg

Hardware-Efficient Neuro-Symbolic Networks with the Exp-Minus-Log Operator

arXiv:2604.13871v1 Announce Type: new Abstract: Deep neural networks (DNNs) deliver state-of-the-art accuracy on regression and classification tasks, yet two structural deficits persistently obstruct

safetyarxiv-cs-lg

IGen: Scalable Data Generation for Robot Learning from Open-World Images

arXiv:2512.01773v2 Announce Type: replace Abstract: The rise of generalist robotic policies has created an exponential demand for large-scale training data. However, on-robot data collection is labor-

safetyarxiv-cs-ro

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

Learning Class Difficulty in Imbalanced Histopathology Segmentation via Dynamic Focal Attention

arXiv:2604.13479v1 Announce Type: cross Abstract: Semantic segmentation of histopathology images under class imbalance is typically addressed through frequency-based loss reweighting, which implicitly

Learning Inference Concurrency in DynamicGate MLP Structural and Mathematical Justification

arXiv:2604.13546v1 Announce Type: new Abstract: Conventional neural networks strictly separate learning and inference because if parameters are updated during inference, outputs become unstable and ev

mLaSDI: Multi-stage latent space dynamics identification

arXiv:2506.09207v4 Announce Type: replace Abstract: Accurately solving partial differential equations (PDEs) is essential across many scientific disciplines. However, high-fidelity solvers can be comp

Multi-Dimensional Knowledge Profiling with Large-Scale Literature Database and Hierarchical Retrieval

arXiv:2601.15170v2 Announce Type: replace Abstract: The rapid expansion of research across machine learning, vision, and language has produced a volume of publications that is increasingly difficult t

node2vec or triangle-biased random walks: stationarity, regularity & recurrence

arXiv:2604.13681v1 Announce Type: cross Abstract: The node2vec random walk is a non-Markovian random walk on the vertex set of a graph, widely used for network embedding and exploration. This random w

Tutorials

Nonparametric Sparse Online Learning of the Koopman Operator

arXiv:2405.07432v4 Announce Type: replace-cross Abstract: The Koopman operator provides a powerful framework for representing the dynamics of general nonlinear dynamical systems. However, existing dat

tutorialsarxiv-cs-lg

Optimized Human-Robot Co-Dispatch Planning for Petro-Site Surveillance under Varying Criticalities

arXiv:2602.07924v2 Announce Type: replace Abstract: Securing petroleum infrastructure requires balancing autonomous system efficiency with human judgment for threat escalation, a challenge unaddressed

agentsarxiv-cs-ro

ParlaSpeech 3.0: Richly Annotated Spoken Parliamentary Corpora of Croatian, Czech, Polish, and Serbian

arXiv:2511.01619v2 Announce Type: replace Abstract: ParlaSpeech is a collection of spoken parliamentary corpora currently spanning four Slavic languages - Croatian, Czech, Polish and Serbian - all tog

researcharxiv-cs-cl

Power Transform Revisited: Numerically Stable, and Federated

arXiv:2510.04995v3 Announce Type: replace Abstract: Power transforms are popular parametric methods for making data more Gaussian-like, and are widely used as preprocessing steps in statistical analys

applicationsarxiv-cs-lg

Radar-Informed 3D Multi-Object Tracking under Adverse Conditions

arXiv:2604.13571v1 Announce Type: new Abstract: The challenge of 3D multi-object tracking (3D MOT) is achieving robustness in real-world applications, for example under adverse conditions and maintain

applicationsarxiv-cs-cv

RadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment

arXiv:2604.13492v1 Announce Type: cross Abstract: Radar is more resilient to adverse weather and lighting conditions than visual and Lidar simultaneous localization and mapping (SLAM). However, most r

Rethinking Uncertainty in Segmentation: From Estimation to Decision

arXiv:2604.13262v1 Announce Type: new Abstract: In medical image segmentation, uncertainty estimates are often reported but rarely used to guide decisions. We study the missing step: how uncertainty m

Robust Energy-Aware Routing for Air-Ground Cooperative Multi-UAV Delivery in Wind-Uncertain Environments

arXiv:2604.13441v1 Announce Type: new Abstract: Ensuring energy feasibility under wind uncertainty is critical for the safety and reliability of UAV delivery missions. In realistic truck-drone logisti

safetyarxiv-cs-ro

Hardware

SemiFA: An Agentic Multi-Modal Framework for Autonomous Semiconductor Failure Analysis Report Generation

arXiv:2604.13236v1 Announce Type: new Abstract: Semiconductor failure analysis (FA) requires engineers to examine inspection images, correlate equipment telemetry, consult historical defect records, a

hardwarearxiv-cs-cv

SuperGrasp: Single-View Object Grasping via Superquadric Similarity Matching, Evaluation, and Refinement

arXiv:2603.29254v2 Announce Type: replace Abstract: Robotic grasping from single-view observations remains a critical challenge in manipulation. However, existing methods still struggle to generate re

applicationsarxiv-cs-ro

Temporally Consistent Long-Term Memory for 3D Single Object Tracking

arXiv:2604.13789v1 Announce Type: new Abstract: 3D Single Object Tracking (3D-SOT) aims to localize a target object across a sequence of LiDAR point clouds, given its 3D bounding box in the first fram

Towards Multi-Object-Tracking with Radar on a Fast Moving Vehicle: On the Potential of Processing Radar in the Frequency Domain

arXiv:2604.14013v1 Announce Type: cross Abstract: We promote in this paper the processing of radar data in the frequency domain to achieve higher robustness against noise and structural errors, especi

agentsarxiv-cs-cv

Local Ai

Weakly-supervised Learning for Physics-informed Neural Motion Planning via Sparse Roadmap

arXiv:2604.13204v1 Announce Type: new Abstract: The motion planning problem requires finding a collision-free path between start and goal configurations in high-dimensional, cluttered spaces. Recent l

local-aiarxiv-cs-ro

A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting

arXiv:2603.10559v2 Announce Type: replace Abstract: This paper studies cross-market return predictability through a machine learning framework that preserves economic structure. Exploiting the non-ove

A Comparison of Reinforcement Learning and Optimal Control Methods for Path Planning

arXiv:2604.12628v1 Announce Type: cross Abstract: Path-planning for autonomous vehicles in threat-laden environments is a fundamental challenge. While traditional optimal control methods can find idea

safetyarxiv-cs-ro

A unified data format for managing diabetes time-series data: DIAbetes eXchange (DIAX)

arXiv:2604.11944v1 Announce Type: new Abstract: Diabetes devices, including Continuous Glucose Monitoring (CGM), Smart Insulin Pens, and Automated Insulin Delivery systems, generate rich time-series d

Agentic LLM Reasoning in a Self-Driving Laboratory for Air-Sensitive Lithium Halide Spinel Conductors

arXiv:2604.11957v1 Announce Type: cross Abstract: Self-driving laboratories promise to accelerate materials discovery. Yet current automated solid-state synthesis platforms are limited to ambient cond

agentsarxiv-cs-lg

AGMA: Adaptive Gaussian Mixture Anchors for Prior-Guided Multimodal Human Trajectory Forecasting

arXiv:2602.04204v2 Announce Type: replace Abstract: Human trajectory forecasting requires capturing the multimodal nature of pedestrian behavior. However, existing approaches suffer from prior misalig

Algorithmic Analysis of Dense Associative Memory: Finite-Size Guarantees and Adversarial Robustness

arXiv:2604.12811v1 Announce Type: cross Abstract: Dense Associative Memory (DAM) generalizes Hopfield networks through higher-order interactions and achieves storage capacity that scales as O(N^{n-1})

researcharxiv-cs-ai

BarbieGait: An Identity-Consistent Synthetic Human Dataset with Versatile Cloth-Changing for Gait Recognition

arXiv:2604.12221v1 Announce Type: new Abstract: Gait recognition, as a reliable biometric technology, has seen rapid development in recent years while it faces significant challenges caused by diverse

applicationsarxiv-cs-cv

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

researcharxiv-cs-ai

CIA: Inferring the Communication Topology from LLM-based Multi-Agent Systems

arXiv:2604.12461v1 Announce Type: new Abstract: LLM-based Multi-Agent Systems (MAS) have demonstrated remarkable capabilities in solving complex tasks. Central to MAS is the communication topology whi

safetyarxiv-cs-ai

Correction of Decoupled Weight Decay

arXiv:2512.08217v3 Announce Type: replace Abstract: Decoupled weight decay, solely responsible for the performance advantage of AdamW over Adam, has long been set to proportional to learning rate gamm

Cross-Modal Knowledge Distillation for PET-Free Amyloid-Beta Detection from MRI

arXiv:2604.12574v1 Announce Type: new Abstract: Detecting amyloid-eta (Aeta) positivity is crucial for early diagnosis of Alzheimer's disease but typically requires PET imaging, which is costly, invas

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

Deep Learning using Rectified Linear Units (ReLU)

arXiv:1803.08375v3 Announce Type: replace-cross Abstract: The Rectified Linear Unit (ReLU) is a foundational activation function in artficial neural networks. Recent literature frequently misattribute

Deepfakes at Face Value: Image and Authority

arXiv:2604.12490v1 Announce Type: cross Abstract: Deepfakes are synthetic media that superimpose or generate someone's likeness on to pre-existing sound, images, or videos using deep learning methods.

researcharxiv-cs-ai

Detecting Precise Hand Touch Moments in Egocentric Video

arXiv:2604.12343v1 Announce Type: new Abstract: We address the challenging task of detecting the precise moment when hands make contact with objects in egocentric videos. This frame-level detection is

DINO-Explorer: Active Underwater Discovery via Ego-Motion Compensated Semantic Predictive Coding

arXiv:2604.12933v1 Announce Type: cross Abstract: Marine ecosystem degradation necessitates continuous, scientifically selective underwater monitoring. However, most autonomous underwater vehicles (AU

agentsarxiv-cs-cv

Distinct mechanisms underlying in-context learning in transformers

arXiv:2604.12151v1 Announce Type: new Abstract: Modern distributed networks, notably transformers, acquire a remarkable ability (termed `in-context learning') to adapt their computation to input stati