Search: “models”

Additive Causal Construction for Transferable and Reconfigurable Cross-System Learning in Multi-Source Image Fusion

arXiv:2607.02572v1 Announce Type: cross Abstract: In multi-source image fusion scenarios, heterogeneous inputs are typically driven by distinct generative mechanisms and can be viewed as a composition

safetyarxiv-cs-ai

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Agents

Agentic and Generative AI for Open-Source Intelligence and Cyber Investigations: Taxonomy, Evaluation, Challenges, and Future Directions

DGX agent

arXiv:2607.03233v1 Announce Type: cross Abstract: The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intel

agentsarxiv-cs-ai

7 Jul 2026

Air Quality Downscaling with Station-Guided Pseudo-Supervision

arXiv:2607.05292v1 Announce Type: cross Abstract: Super-resolving coarse atmospheric fields to local PM_{2.5} variations is uniquely challenged by a mismatch in spatial support: while pixels represent

Aircraft Detection in Satellite Imagery using Deep Learning Object Detectors

arXiv:2607.02699v1 Announce Type: new Abstract: The object detection in satellite imagery has garnered considerable attention due to its extensive real-world applications and the inherent challenges i

tutorialsarxiv-cs-cv

An event-driven framework for fly-inspired visual motion detection

arXiv:2607.05205v1 Announce Type: new Abstract: Fast and reliable motion detection is essential for machine vision and autonomous systems operating in dynamic environments. This work integrates emergi

agentsarxiv-cs-cv

Aura: Consistent Multi-Subject Video Generation via VLM-Grounded Semantic Alignment

arXiv:2607.04311v1 Announce Type: new Abstract: Subject-driven and multi-element video generation are central to controllable video synthesis, but existing methods still struggle to preserve identity

Can Dialects Be Steered Like Languages? Sparse Neurons and Distributed Directions in Arabic LLMs

arXiv:2607.03936v1 Announce Type: new Abstract: A key challenge in Arabic NLP is the scarcity of dialectal data relative to Modern Standard Arabic (MSA), causing LLMs to overproduce MSA and struggle w

researcharxiv-cs-cl

CaresAI at SMM4H-HeaRD 2026: Predicting TNM Staging

arXiv:2607.03466v1 Announce Type: cross Abstract: This study aims to predict Tumor, Node, and Metastasis (TNM) stage labels independently, with the Cancer Genome Atlas (TCGA) pathology report as the s

applicationsarxiv-cs-ai

Causal-RetiGraph: Cross-Cohort Retinal Support and Same-Subject Pathway Analysis for Diabetic Retinopathy

arXiv:2607.05204v1 Announce Type: new Abstract: Diabetic retinopathy (DR) is a local retinal lesion process and a visible manifestation of systemic microvascular injury. Modern retinal AI can grade im

local-aiarxiv-cs-cv

City landscape in sight: A crowdsourced framework for unlocking urban-scale window view perceptions from real estate imagery

arXiv:2606.15198v2 Announce Type: replace Abstract: City landscapes viewed through home windows influence quality of life, yet perceptions of actual window views at the urban scale remain understudied

CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving

arXiv:2607.02841v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E-AD) aims to directly map raw sensor information to driving actions. Recently, with the rapid advancement of multi-m

Closing the Reality Gap: Zero-Shot Sim-to-Real Deployment for Dexterous Force-Based Grasping and Manipulation

arXiv:2607.04940v1 Announce Type: new Abstract: Human-like dexterous hands with multiple fingers offer human-level manipulation capabilities but remain difficult to train the control policies that can

applicationsarxiv-cs-ro

CodeJeNN: A simple C++ neural network generator for physics applications

arXiv:2607.02746v1 Announce Type: cross Abstract: Machine learning has shown speedups for numerical methods in physics applications, but integrating Python-based libraries into high-performance C++ so

CoFEND: A Cross-Modal Fusion End-to-End Network for Cold-Start Drug-Drug Interaction Prediction

arXiv:2607.02928v1 Announce Type: new Abstract: Cold-start drug-drug interaction (DDI) prediction for new drugs is critical for minimizing unexpected adverse drug reactions. The key challenge is to ca

CogRad: A Cognitively-Inspired Multi-Agent Framework for Radiology Report Generation

arXiv:2607.03853v1 Announce Type: new Abstract: Automated radiology report generation (RRG) can ease radiologist workload, yet most existing systems produce a report in a single forward pass, with no

agentsarxiv-cs-cv

Compressed Computation under L^4 Loss is likely Computation in Superposition

arXiv:2607.04800v1 Announce Type: new Abstract: Neural networks are thought to represent concepts as directions in their activation space, and superposition lets them encode more concepts than they ha

Conversational Human Audio-visual Talking Dialogue Generation

arXiv:2607.02799v1 Announce Type: new Abstract: Large-scale dyadic interactive audio-visual dialogue (DIAD) datasets provide fundamental data resources for developing humanoid interactive virtual agen

CoorGrasp: Coordinated Contact Control for Adaptive Dexterous Grasping Under Uncertainty

arXiv:2607.03557v1 Announce Type: new Abstract: While recent research has focused heavily on dexterous grasp pose generation, less attention has been devoted to the execution of planned grasps. Under

applicationsarxiv-cs-ro

CORA: Generalizable coronary artery disease assessment and risk stratification from coronary CT angiography using pathology-centric representation learning

arXiv:2603.24847v2 Announce Type: replace Abstract: Coronary artery disease, a leading cause of cardiovascular mortality worldwide, can be assessed non-invasively by coronary computed tomography angio

local-aiarxiv-cs-cv

Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks

arXiv:2603.14830v3 Announce Type: replace Abstract: Dataset distillation, a training-aware data compression technique, has recently attracted increasing attention as an effective tool for mitigating c

DeGenseGS: Geometrically and Semantically Decoupled Surgical Scene Understanding in 4D Gaussian Splatting

arXiv:2607.04761v1 Announce Type: new Abstract: Real-time, text-promptable 4D reconstruction is indispensable for autonomous surgical interaction. Severe misalignment between semantic meaning and phys

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)

arXiv:2607.04223v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) reduces but does not eliminate hallucination, and existing detectors return a single answer-level score that does

DGSeg: Dynamic Gating of Semantic-Spatial Guided Predictions for Reasoning Segmentation

arXiv:2607.04779v1 Announce Type: new Abstract: Reasoning segmentation aims to predict pixel-wise masks for targets given complex language queries. Existing approaches leverage Multimodal Large Langua

tutorialsarxiv-cs-cv

Diffusion-Guided Uncertainty-Aware Delayed Policy Optimization

arXiv:2607.05064v1 Announce Type: new Abstract: Reinforcement learning in real world environments often suffers from severe performance degradation due to delayed feedback. Existing approaches typical

safetyarxiv-cs-ai

DIRA-SS:Dynamic Domain Incremental Regularised Adaptation -- Self-Supervised

arXiv:2311.07461v3 Announce Type: replace Abstract: Autonomous systems (AS) often rely on Deep Neural Network (DNN) classifiers to operate in complex and dynamically changing environments. However, du

agentsarxiv-cs-lg

Enhanced Feature Extraction for IoT Network Intrusion Detection Using GNNs and KAN

arXiv:2607.02981v1 Announce Type: cross Abstract: Recent advancements in the Internet of Things (IoT) emphasize the urgent need for advanced network security, as IoT networks feature dynamic topologie

Enhancing Monocular 3D Hand Reconstruction with Learned Texture Priors

arXiv:2508.09629v2 Announce Type: replace Abstract: We revisit the role of texture in monocular 3D hand reconstruction, not as an afterthought for photorealism, but as a dense, spatially grounded cue

Entropy-Coded MS-VQ-VAE with Learned Priors for Ultra-Low Bitrate Video Compression

arXiv:2607.02562v1 Announce Type: new Abstract: Learned video codecs based on continuous latent representations struggle to operate reliably below 0.1 bits per pixel~(bpp): without a differentiable ra

EPRA U-Net: An Efficient Pyramid Residual Attention Framework for Accurate Infarct Segmentation in Diffusion-Weighted MRI

arXiv:2607.03568v1 Announce Type: cross Abstract: Objective: Accurate identification of acute ischemic infarcts on diffusion-weighted magnetic resonance imaging (DWI) is a critical prerequisite for re

Evaluating Generative Agents with Actions Grounded in Socially Distributed Task Environments using Incognita

arXiv:2607.02975v1 Announce Type: new Abstract: Effective agency in social environments depends on when an agent seeks knowledge, when it acts, and whether its actions are justified by acquired inform

agentsarxiv-cs-ai

EvoOtter: Evolutionary Reproduction Test Generator

arXiv:2607.02854v1 Announce Type: cross Abstract: Before fixing an issue, it is useful to first reproduce it by generating a bug reproduction test (BRT). However, generating a BRT is itself a challeng

tutorialsarxiv-cs-lg

Exploring Context-aware and LLM-driven Locomotion for Immersive Virtual Reality

arXiv:2504.17331v3 Announce Type: replace-cross Abstract: Locomotion plays a crucial role in shaping the user experience within virtual reality environments. In particular, hands-free locomotion offer

FedSPM: Routing-Enabled Federated Learning under Dual Heterogeneity via Semiparametric Mixture

arXiv:2607.04085v1 Announce Type: cross Abstract: Routing-prediction federated learning has emerged as a new paradigm that reframes inter-client heterogeneity as a resource for system-level intelligen

Fine-Grained Computation Offload for Off-the-Shelf Servers in Tens of Lines

arXiv:2607.02630v1 Announce Type: cross Abstract: Hardware accelerators now sit on the critical path of online serving. GPUs, FPGAs, and increasingly remote services such as hardware security modules,

applicationsarxiv-cs-ai

FRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion

arXiv:2607.04125v1 Announce Type: new Abstract: Small object detection in Unmanned Aerial Vehicle (UAV) imagery remains challenging under adverse conditions, including complex weather, low illuminatio

From Mobile Data to Business Insights: An End-to-End Analytics Framework for Large-Scale Urban Mobility Analysis and Decision Support

arXiv:2607.03394v1 Announce Type: new Abstract: Real time location data derived from mobile applications is a powerful tool for addressing various urban challenges, including tourism planning, parking

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection

arXiv:2607.05176v1 Announce Type: new Abstract: Small object detection (SOD) remains a challenging task in real-world applications. Despite recent advances, existing detectors remain limited by rigid

applicationsarxiv-cs-cv

Function-Space Diffusion for Motion Planning

arXiv:2607.02977v1 Announce Type: new Abstract: Diffusion-based motion planners have demonstrated strong performance in generating diverse and high-quality robot trajectories in cluttered environments

researcharxiv-cs-ro

GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks

arXiv:2607.05369v1 Announce Type: cross Abstract: For robots to work reliably in commercial and industrial applications, can recent advances in agentic coding systems combine interpretable robot progr

safetyarxiv-cs-ai

Generative Pseudo-Labeling for Pre-Ranking with LLMs

arXiv:2602.20995v2 Announce Type: replace-cross Abstract: Pre-ranking is a critical stage in industrial recommendation systems, tasked with efficiently scoring thousands of recalled items for downstre

safetyarxiv-cs-cl

Geometry-Aware Bayesian Quantification via Compositional Data Analysis

arXiv:2607.04977v1 Announce Type: new Abstract: Accurately estimating the unknown target label distribution is the critical first step for adapting to label shift. This task, widely known as quantific

Global Pose Control for Generative View Synthesis in Normalized Object Coordinate Space

arXiv:2607.02712v1 Announce Type: new Abstract: Novel View Synthesis (NVS) enables the generation of unseen views of a scene from a single or multiple images, allowing users to freely explore an objec

GPU-Accelerated Polygonal Signed Distance Functions for Real-Time Collision Avoidance

arXiv:2607.04310v1 Announce Type: new Abstract: Optimization-based local planning and control require high-rate collision-avoidance constraint evaluation over a prediction horizon. In obstacle-dense e

local-aiarxiv-cs-ro

Graph Neural Networks are Heuristics

arXiv:2601.13465v4 Announce Type: replace Abstract: Graph neural networks are usually treated as auxiliaries for combinatorial optimization: they imitate algorithms, guide search, or supply scores to

GRCD: Grounded Region Change Detection for Multi-Finding Chest X-Ray Pairs

arXiv:2607.02719v1 Announce Type: new Abstract: Radiologists routinely compare current and prior chest X-rays to track disease progression, producing follow-up reports that describe multiple findings,

local-aiarxiv-cs-cv

Harmonic-Aware Transformer for Real-Time Catheter Localization in Interventional Procedures of Magnetic Particle Imaging

arXiv:2607.02919v1 Announce Type: cross Abstract: Magnetic particle imaging (MPI) enables real-time, radiation-free tracking of magnetic nanoparticle-coated instruments, making it highly suitable for

Hierarchical Scaffolding Enables Human-Like Cognitive Selectivity under Data Scarcity

arXiv:2607.04709v1 Announce Type: cross Abstract: Modern machine learning systems demand extensive datasets for visual recognition. Conversely, humans learn with high efficiency despite severe data li

tutorialsarxiv-cs-cv

Individual Parameters in Weight-Sparse Transformers Appear Interpretable

arXiv:2607.02964v1 Announce Type: cross Abstract: A central goal of mechanistic interpretability is to understand how neural networks work and what each individual component does. Dominant circuit-fin