Search: “models”

The Perils of Agency: How Developers Perceive, Prioritize, and Address Risks in Agentic AI Products

arXiv:2606.15485v2 Announce Type: replace-cross Abstract: Agentic AI systems act autonomously, use tools, adapt to context, and operate in complex real-world environments. However, these same characte

10 Aug 2026

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Understand Before Detect: Vision--Language Learning for Omni-Domain Infrared Small Target Detection

DGX agent

arXiv:2608.07015v1 Announce Type: new Abstract: Omni-domain infrared small target (IRST) detection is crucial for infrared surveillance, yet remains challenging due to heterogeneous imaging domains an

researcharxiv-cs-cv

10 Aug 2026

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning

arXiv:2608.06934v1 Announce Type: cross Abstract: Visual perception of walkability varies substantially across individuals, reflecting differences in personal characteristics, experiences, and prefere

10 Aug 2026

A Study of ASR Adaptation and Representation Dimensionality Reduction in Persian Speech Emotion Recognition Using Whisper

arXiv:2608.05165v1 Announce Type: cross Abstract: Speech Emotion Recognition (SER) in low-resource languages remains a challenging problem due to limited labeled data. In this work, we study the use o

Analogy as Nonparametric Bayesian Inference over Relational Systems

arXiv:2006.04156v2 Announce Type: replace Abstract: Our inferences in the real world are rarely naive - we acquire experiences through our lifetime that can help us more quickly understand the structu

tutorialsarxiv-cs-ai

APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning

arXiv:2608.05499v1 Announce Type: cross Abstract: Modern deep neural networks achieve strong performance, but their scale makes them costly and slow, especially on resource-constrained edge devices. P

Bayesian adaptively-weighted ensembles for few-shot abdominal segmentation

arXiv:2608.05815v1 Announce Type: new Abstract: Few-shot learning has emerged as a promising approach for anatomical segmentation when labelled data are scarce. However, different few-shot learning al

Local Ai

Beyond Feature Importance: A Comparative Analysis of Pattern Detection Methods in Cluster Interpretation

arXiv:2608.05880v1 Announce Type: cross Abstract: Interpreting clustering outcomes remains a fundamental challenge in data analysis, particularly in domains such as healthcare where meaningful pattern

local-aiarxiv-cs-ai

BioKD: Selective Physiology-to-Video Knowledge Distillation via Reliability Gate for Emotion Recognition

arXiv:2608.06023v1 Announce Type: new Abstract: To address the limitations of video-based emotion recognition under ambiguous or socially masked behavioral cues, as well as the poor deployability of p

tutorialsarxiv-cs-lg

CalibForge: Adversarial Solver Calibration for Scaling Learnable Terminal Tasks

arXiv:2608.06352v1 Announce Type: cross Abstract: Training terminal agents requires executable and verifiable tasks that are not merely solvable, but appropriately challenging for learning. Executable

agentsarxiv-cs-cl

CFGPNet: Cross-Attention-Based Fused Gradient Programmed Network Framework for Multispectral Object Detection

arXiv:2608.06205v1 Announce Type: new Abstract: RGB--T object detection exploits the complementary strengths of visible and infrared imagery, supporting robust perception in low-light, adverse-weather

Decolonizing Linguistic Policies in Automated Speech Recognition: A Framework for Cross-Culturally Competent Speech AI

arXiv:2608.06141v1 Announce Type: new Abstract: This paper focuses on automatic speech recognition (ASR) and ASR-mediated voice interfaces that shape access to public services, healthcare, and educati

safetyarxiv-cs-cl

DistMedVL: Distributional Vision-Language Alignment for Uncertainty-Aware Medical Image Segmentation

arXiv:2608.05683v1 Announce Type: cross Abstract: Cross-modal alignment of visual and textual representations is fundamental to multimodal medical image understanding, yet remains hindered by uncertai

safetyarxiv-cs-ai

Does FLAIR super-resolution erase or hallucinate small white-matter lesions?

arXiv:2608.06311v1 Announce Type: cross Abstract: White matter hyperintensities (WMH), bright regions on Fluid-attenuated Inversion Recovery (FLAIR) scans are associated with cerebrovascular pathology

Local Ai

ECG-LENS: Lead-Aware Clinical Context Enriched ECG Report Generation and Evaluation

arXiv:2608.05893v1 Announce Type: new Abstract: Electrocardiography (ECG) is one of the most widely used non-invasive tools for diagnosing cardiovascular disease, but transforming multi-lead ECG recor

local-aiarxiv-cs-ai

F^2Agent: Financial Fusion of Agentic Intelligence for Multimodal Trading

arXiv:2608.05668v1 Announce Type: cross Abstract: With increasingly diverse and heterogeneous information sources, effectively leveraging multimodal data is becoming pivotal for high-quality financial

GenGA: Editable and Data-Grounded Graphical Abstract Generation for Academic Papers

arXiv:2608.05478v1 Announce Type: cross Abstract: Graphical Abstracts (GAs) visually summarize the key findings of academic papers, playing a crucial role in facilitating the understanding of research

safetyarxiv-cs-cl

Handling Missing Data in Probabilistic Regression Trees

arXiv:2608.06195v1 Announce Type: cross Abstract: Probabilistic Regression Trees (PRTrees) are a smooth and consistent alternative to classical regression trees, producing continuous predictions throu

applicationsarxiv-cs-lg

Hierarchical Flow Matching for 3D Point Cloud Generation

arXiv:2608.05557v1 Announce Type: new Abstract: Generating high-quality 3D point clouds requires capturing both global shape topology and local geometric details. Existing flow-based methods rely on c

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs

arXiv:2608.05759v1 Announce Type: new Abstract: Recognizing new and rare words - named entities, acronyms, domain specific special words, and other items scarce in training data - remains a key challe

tutorialsarxiv-cs-cl

Hybrid Machine Learning Framework for Herd-Level Cattle Growth Pattern and Weight Gain Forecasting in Grazing-Based Production Systems

arXiv:2608.06001v1 Announce Type: new Abstract: Commercial grazing systems yield irregular livestock observations, which challenge cattle growth forecasting. This study developed a hybrid machine lear

applicationsarxiv-cs-ai

LiteKD-Net: Lightweight Knowledge-Distilled Network for Mobile Image Denoising

arXiv:2608.05739v1 Announce Type: new Abstract: Mobile image denoising requires both good restoration quality and low computational cost. In addition, it's annoying to collect large-scale LQ-GT clean

applicationsarxiv-cs-cv

Mapping Armenian Paris: Extracting and Geocoding Commercial Advertisements from the 20th-Century Diaspora Press

arXiv:2608.05911v1 Announce Type: new Abstract: This paper presents an end-to-end, IIIF-based pipeline that turns the digitised Armenian press of France into an interactive map of the 20th-century Par

Mapping Patient-Perceived Physician Traits from Nationwide Online Reviews with LLMs

arXiv:2510.03997v2 Announce Type: replace Abstract: Understanding how patients perceive their physicians is essential to improving trust, communication, and satisfaction. Patients increasingly consult

safetyarxiv-cs-cl

MapTCL: Temporal Consistency Learning via Bidirectional Alignment for Vectorized HD Map Construction

arXiv:2608.05209v1 Announce Type: new Abstract: Constructing reliable online HD maps remains challenging in dynamic urban environments due to moving objects and occlusions. While recent works employ f

safetyarxiv-cs-cv

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification

arXiv:2608.06250v1 Announce Type: cross Abstract: In overparameterised classification, training data can be linearly separable even when the underlying distribution is not. In this setting, gradient d

safetyarxiv-cs-lg

MirrorNet: Can Medical Image Anonymization Really Protect Patient Identity?

arXiv:2608.05938v1 Announce Type: new Abstract: Medical images are routinely de-identified---names, dates, and other metadata removed---and then shared for research, teaching, and public benchmarks un

Multivariate Time Series Forecasting needs Cross Variable Loss

arXiv:2608.05742v1 Announce Type: cross Abstract: Multivariate time series forecasting presents unique challenges because future variables often co-evolve under shared system dynamics. While existing

Observation-Grounded Self-Predictive Reinforcement Learning for Visual Continuous Control

arXiv:2608.05989v1 Announce Type: new Abstract: Sample-efficient policy learning from pixels is a long-standing challenge in reinforcement learning (RL). Recent dynamics-based representation learning

safetyarxiv-cs-lg

One Qubit Can Beat One Bit: Quantum Advantage for Post-Training Quantization

arXiv:2608.05240v1 Announce Type: cross Abstract: One-bit post-training quantization represents each weight using only its sign, requiring all deployment contexts to share the same binary weight matri

Ordered Diffusion for 3D Human Registration

arXiv:2608.05804v1 Announce Type: new Abstract: 3D human registration has historically been treated as a regression task, assuming a unique ground-truth alignment exists between the template and an in

safetyarxiv-cs-cv

OTLesMix: Wasserstein Barycenter and Optimal Transport Map for Synthetic Lesion Generation with Diverse Shapes and Locations

arXiv:2608.06264v1 Announce Type: new Abstract: The development of deep learning over the past decade has revolutionized medical imaging segmentation, allowing the extraction of precise descriptors fr

Path Planning of Cleaning Robot with Reinforcement Learning

arXiv:2208.08211v2 Announce Type: replace-cross Abstract: Recently, as the demand for cleaning robots has steadily increased, therefore household electricity consumption is also increasing. To solve t

safetyarxiv-cs-ai

Potential Matching Optimal Transport: Continuous Normalizing Flows for Exact p-Wasserstein Dynamics

arXiv:2608.05666v1 Announce Type: new Abstract: We introduce Potential Matching Optimal Transport (PMOT), a potential-flow framework for general p-cost optimal transport with c_p(x,y)=|x-y|^p. PMOT pa

researcharxiv-cs-lg

RA-CAD: Learning Post-Execution Critique for State-Aware Text-to-CAD Generation

arXiv:2608.05714v1 Announce Type: new Abstract: Text-to-CAD generation translates natural-language design intent into editable and executable parametric computer-aided design (CAD) codes, reducing the

safetyarxiv-cs-ai

Refining Over Resampling: Test-Time Self-Correction for LLM Reasoning

arXiv:2608.05643v1 Announce Type: new Abstract: Test-time scaling improves LLM reasoning by using additional inference compute, but wider sampling alone can suffer from diminishing returns: new rollou

Reinforcing Action Policies by Prophesying

arXiv:2511.20633v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) policies excel in aligning language, perception, and robot control. However, most VLAs are trained purely by imitation,

tutorialsarxiv-cs-ro

Spectral Aliasing Pretext: A novel task for Self-Supervised fault diagnosis in rotating machinery

arXiv:2608.05705v1 Announce Type: cross Abstract: Deep learning is a new way for machinery fault diagnosis but requires extensive labeled data, a scarce resource in industrial settings. We propose Spe

tutorialsarxiv-cs-ai

Stochastic Dynamics on Persistence Diagram Space via Reinforcement Learning

arXiv:2608.06276v1 Announce Type: cross Abstract: Persistence diagrams (PDs) provide stable and interpretable summaries of multiscale topological structure. While substantial progress has been made in

tutorialsarxiv-cs-lg

Topology-Aware Neighborhood Learning for Source-Free Cross-Scene Hyperspectral Image Classification

arXiv:2608.05964v1 Announce Type: new Abstract: Domain adaptation has advanced cross-scene hyperspectral image classification, significantly improving discriminative capability in complex scenarios. H

VIDP: Variable Impedance Diffusion Policy for Compliant Robot Manipulation from Diverse Demonstrations

arXiv:2608.06210v1 Announce Type: new Abstract: Contact-rich manipulation requires precise tracking and mechanical compliance, where variable impedance control can improve robustness in task success,

safetyarxiv-cs-ro

Vorch-IR: Long-Form Unified Multimodal Identity Replacement Video Generation

arXiv:2608.05648v1 Announce Type: new Abstract: Video identity replacement seeks to transfer the identities of one or more subjects while preserving the motion, expressions, and temporal structure of

When Agentic AI Meets Integrated Sensing and Communication

arXiv:2608.05792v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) is transforming Integrated Sensing and Communication (ISAC) from a function-oriented physical-layer technology into

Hardware

AI-based single-shot structured-light depth reconstruction for real-time laparoscopic surgical guidance

arXiv:2608.05109v1 Announce Type: cross Abstract: Significance. Accurate intraoperative depth perception is important for autonomous and semi-autonomous robotic laparoscopic surgery. Conventional frin

hardwarearxiv-cs-ro

Bag-of-Visual-Words for Spatial Mapping of Lung Adenocarcinoma Growth Patterns

arXiv:2608.05074v1 Announce Type: new Abstract: Spatial mapping of lung adenocarcinoma (LUAD) growth patterns across whole slide images (WSIs) requires resolving architectural context at the region le

Local Ai

Beyond Motion Cues and Structural Sparsity: Revisiting Small Moving Target Detection

arXiv:2509.07654v2 Announce Type: replace Abstract: Small moving target detection is crucial for many defense applications but remains highly challenging due to low signal-to-noise ratios, ambiguous v

local-aiarxiv-cs-cv

Beyond Reprojection Error: Camera Calibration with 3D Targets

arXiv:2608.05066v1 Announce Type: new Abstract: In 3D reconstruction, camera calibration is an essential element for achieving high fidelity and accuracy of the reconstructed geometry. While existing

CAMP: A Cycle-Aware Multi-Scale Patch Mixer for Time Series Forecasting

arXiv:2608.04051v1 Announce Type: new Abstract: Real-world time series are often governed by recurring patterns, but their dominant periods may vary across datasets, forecasting settings, and individu

applicationsarxiv-cs-lg