Search: “models”

Multimodal Ambivalence and Hesitancy Recognition via Cross-Attention and Gated Fusion

arXiv:2607.15779v2 Announce Type: replace Abstract: We present a multimodal framework for Ambivalence/Hesitancy (A/H) recognition in video, developed for the ABAW11 challenge at ECCV 2026. The propose

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Multiple Scale Latents for Learned Image Compression

DGX agent

arXiv:2608.10952v1 Announce Type: new Abstract: Most learned image compression systems rely on a single latent representation combined with a hyperprior, which limits their ability to efficiently capt

researcharxiv-cs-cv

12 Aug 2026

Physics-Informed Machine Learning in Prognostics and Health Management: A Systematic Literature Review

arXiv:2608.10047v1 Announce Type: cross Abstract: In modern industry, keeping complex systems reliable, safe, and efficient hinges on Prognostics and Health Management (PHM). Machine Learning (ML) has

Pre- to Post-Contrast Synthesis of Breast DCE-MRI using Latent Bridge Matching

arXiv:2608.10000v1 Announce Type: cross Abstract: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is central to breast cancer imaging, but gadolinium administration increases scan burde

Predicting Space Groups of Double Perovskites by LLM with Dynamic Few-Shot Learning

arXiv:2608.10483v1 Announce Type: new Abstract: Double perovskites (DPs) offer broad compositional tunability, but predicting the space groups (SGs) of stable structures remains difficult because avai

Recovering Wasted Compute in Autoresearch Agents

arXiv:2608.10424v1 Announce Type: new Abstract: A slew of recent works develop agents for solving research problems end-to-end, a paradigm increasingly referred to as autoresearch. Such agents have in

SpecF2M: A Spectral-Aware Multi-task Network Estimating Axial Length and Refractive Error from Pediatric Fundus Photographs

arXiv:2608.09994v1 Announce Type: cross Abstract: Spherical Equivalent Refraction (SER) and Axial Length (AL) are core indicators for pediatric myopia screening, yet their measurements require dedicat

Spectral Embeddings of Degree-alpha Laplacians in Random Dot Product Graphs

arXiv:2608.10845v1 Announce Type: cross Abstract: Spectral clustering methods for network data are commonly based on a few matrix representations, such as the adjacency matrix and the symmetric Laplac

SPOTting the Future: Lookahead Explanations for Deep Reinforcement Learning

arXiv:2608.09967v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) agents achieve strong performance in complex environments, yet their decision-making processes remain difficult to int

STCAD: Scalable Trajectory Clustering and Anomaly Detection on Terabyte-Scale AIS Data

arXiv:2608.10249v1 Announce Type: new Abstract: We present a scalable framework for unsupervised clustering of maritime trajectories derived from terabyte-scale Automatic Identification System (AIS) a

SuperQuadricOcc: Real-Time Self-Supervised Semantic Occupancy Estimation with Superquadric Volume Rendering

arXiv:2511.17361v5 Announce Type: replace Abstract: Self-supervision for semantic occupancy estimation is appealing as it removes the labour-intensive manual annotation, thus allowing one to scale to

agentsarxiv-cs-cv

The CASE Framework: A Multi-Disciplinary Control Architecture for Governing Enterprise Agentic AI

arXiv:2608.10153v1 Announce Type: new Abstract: Enterprises are deploying autonomous AI agents faster than they can govern them, and prevailing approaches stretch a single discipline, typically DevSec

The Deliberative Deficit: An Empirical Critique of LLMs in Democratic Discourse

arXiv:2608.10186v1 Announce Type: cross Abstract: LLMs are increasingly deployed in settings that require collective reasoning on complex, value-laden problems. Confidence in these deployments rests l

The Hidden Puppet Master: Predicting Human Belief Change in Manipulative LLM Dialogues

arXiv:2603.20907v5 Announce Type: replace Abstract: As users increasingly turn to LLMs for practical and personal advice, they become vulnerable to subtle steering toward hidden incentives misaligned

safetyarxiv-cs-cl

Threat-guided Policy-aware Scene Perturbation for Safe Autonomous Driving with Online Reinforcement Learning

arXiv:2608.10403v1 Announce Type: new Abstract: Reinforcement learning (RL) has shown promising performance in autonomous driving, yet ensuring the safety of online RL policies remains challenging due

TimeRoute: Time-Aware Modality Routing and Diffusion for Multi-Modal Recommendation

arXiv:2608.10983v1 Announce Type: cross Abstract: Multi-modal recommenders fuse collaborative signals with item modalities such as text, images, and audio, but the usefulness of each drifts over time

Towards Color-Faithful Low-Light Image Enhancement via Adaptive Color Debiasing and Saturation Rectification

arXiv:2608.10512v1 Announce Type: new Abstract: Low-light imaging often introduces color bias caused by the low signal-to-noise ratio and the image formation process. Although recent low-light image e

safetyarxiv-cs-cv

When Do Anchor-Based Pointwise LLM Rerankers Help? Retriever Quality, Statistical Scope, and Anchor Design

arXiv:2608.10528v1 Announce Type: cross Abstract: Anchor-based pointwise LLM reranking scores each candidate against a shared reference passage to recover cross-document context at pointwise cost. We

Applications

When Repository Labels Are Not Image-Level Truth: A Supervision Auditing Framework for Chest Radiograph AI

arXiv:2608.10084v1 Announce Type: cross Abstract: Public chest X-ray repositories are widely used to train medical AI systems, yet their labels are typically extracted from radiology reports rather th

applicationsarxiv-cs-cv

Wind-Informed Rapid Flight-Planning in Complex Urban Topologies via Machine Learning and Experimental Validation

arXiv:2608.10309v1 Announce Type: cross Abstract: Advanced air mobility operations hold the potential to enhance and expand regional transportation of both people and goods in populated areas. However

researcharxiv-cs-ro

A Machine Learning Based Search for Lunar Anomalies

arXiv:2608.09350v1 Announce Type: cross Abstract: The Lunar Reconnaissance Orbiter (LRO) has been collecting high-resolution images (at around 0.5-2 meters per pixel linearly with its Narrow Angle Cam

A QUBO-Inspired Computational Framework for Airport Landside Bottleneck Diagnosis and Dynamic Dispatch Optimization

arXiv:2608.08632v1 Announce Type: new Abstract: Airport landside traffic centers connect terminal arrivals with taxis, ride-hailing vehicles, private cars, buses, metro services, parking facilities, a

A Review of Vision-Based Vehicle Detection for UAV-Based Traffic Monitoring: Experimental Insights and Future Directions

arXiv:2608.07571v1 Announce Type: new Abstract: In Intelligent Transportation System (ITS), unmanned aerial vehicle (UAV)-based surveillance offers an innovative solution to traffic surveillance with

A Unified Framework for Dynamic Reward Shaping in Reinforcement Learning

arXiv:2608.08158v1 Announce Type: new Abstract: Sparse, delayed, and weakly informative rewards remain central obstacles to efficient reinforcement learning. Reward shaping addresses these limitations

Adaptive KappaSharp: Condition-Number Shaping for Preferential Bayesian Optimization

arXiv:2608.07859v1 Announce Type: new Abstract: Preferential Bayesian optimization (PBO) optimizes objectives accessible only through pairwise user comparisons. The standard approach fits a Gaussian p

Adaptive Sequential Test Planning for Multi-Mechanism Reliability Qualification via Bayesian Monte Carlo Tree Search

arXiv:2608.09622v1 Announce Type: new Abstract: Reliability qualification of advanced semiconductor devices requires sequential stress decisions that balance characterization objectives against multip

Alpha as an Efficiency Signal: Visibility-Routed RGBA Image-to-Video Generation

arXiv:2608.09355v1 Announce Type: new Abstract: RGBA videos combine RGB appearance with an alpha channel, enabling animated assets to be applied across arbitrary backgrounds, which are heavily used in

Application of Artificial Intelligence for Fraudulent Banking Operations Recognition

arXiv:2608.07471v1 Announce Type: cross Abstract: This study considers the task of applying artificial intelligence to recognize bank fraud. In recent years, due to the COVID19 pandemic, bank fraud ha

Hardware

Beyond Isotropic Assumptions: Continuity-Constrained Segmentation and GPU Morphometry for Nanoscale GBM Analysis

arXiv:2608.07575v1 Announce Type: new Abstract: Confocal microscopy of optically cleared and swelled tissue resolves complex biological structures in 3D, but such acquisitions are highly anisotropic:

hardwarearxiv-cs-cv

Local Ai

Beyond Uniform Restoration: Empowering All-in-One Restoration with Pixel-Level Multimodal Guidance

arXiv:2608.09482v1 Announce Type: cross Abstract: All-in-one image restoration is a unified low-level vision task that aims to effectively recover high-quality images from inputs degraded by various t

local-aiarxiv-cs-ai

Bridging Object Detection and Segmentation with Polygon Detection Transformers

arXiv:2603.09245v2 Announce Type: replace Abstract: Box detection and mask segmentation are two dominant paradigms for foreground representation: boxes are efficient but too coarse for object shapes,

agentsarxiv-cs-cv

Applications

Bridging the Gap Between Semantics and Reconstruction:Unifying Sign Language Translation and Production

arXiv:2608.09045v1 Announce Type: cross Abstract: Recent advances in sign language (SL) research have shown a trend toward unifying multiple sign language understanding (SLU) subtasks, such as isolate

applicationsarxiv-cs-ai

Local Ai

Bright-Channel Retinex Enhancement with a Conditional Overdispered-Noise Analysis

arXiv:2608.09137v1 Announce Type: new Abstract: I present a training-free low-light enhancement method that combines local bright-channel illumination estimation, Retinex division, and edge-preserving

local-aiarxiv-cs-cv

Business Arena: Benchmarking LLM Agents in a Realistic Marketplace

arXiv:2608.08621v1 Announce Type: new Abstract: Running a business is a challenging form of intelligent work. Operators must infer opportunities from partial signals, commit capital under uncertainty,

Business Truth, not SQL Accuracy: A Rule-Gated 7B Analytics Agent Outperforms a Direct-Prompted 32B Baseline

arXiv:2608.09254v1 Announce Type: new Abstract: LLM analytics agents are evaluated on SQL syntax accuracy, but production failures look different: questions with two valid business definitions, questi

City Sentinel: A Unified AI-Based Smart Surveillance Framework for Real-Time Multi-Threat Detection Using Deep Learning

arXiv:2608.08887v1 Announce Type: new Abstract: Rapid urbanization has increased the need for surveillance systems that can monitor multiple public safety risks at the same time. Traditional systems o

safetyarxiv-cs-cv

CoCoNav: Conformal Control for Safe Robot Navigation in Crowds

arXiv:2608.07751v1 Announce Type: cross Abstract: Safe and efficient robot navigation in crowds requires anticipating pedestrian motion despite uncertain and potentially shifting prediction errors. Ex

Compositional Threat Analysis of Latent Compromise in LLM Agent Systems: The Order 66 Scenario

arXiv:2608.08131v1 Announce Type: cross Abstract: In the fictional Order 66, catastrophe does not arise from a powerful command alone: a trusted population is preconditioned, a short directive activat

Crowd-Sourced Geographies of Income: Using Google Maps Points of Interest as High-Frequency Proxies for Sub-Municipal Income Estimation in Sao Paulo, Brazil

arXiv:2608.07871v1 Announce Type: cross Abstract: Accurate, up-to-date income data at the sub-municipal scale is essential for social policy in middle-income countries, yet in Brazil it depends on a c

safetyarxiv-cs-lg

CyberAGENTS: Structured Autonomy for Agentic Gamified Learning in Cybersecurity

arXiv:2608.07965v1 Announce Type: new Abstract: Gamification is especially effective in learning domains requiring active problem-solving and iterative skill-building, such as cybersecurity education.

Dense Point-to-Mask Optimization with Reinforced Point Selection for Crowd Instance Segmentation

arXiv:2604.01742v2 Announce Type: replace Abstract: Crowd instance segmentation is a crucial task with a wide range of applications, including surveillance and transportation. Currently, point labels

safetyarxiv-cs-cv

Designing for Ethical AI: HCI Feature Considerations to Improve Fairness and User Experience in AutoML use for Human Resources

arXiv:2608.07477v1 Announce Type: cross Abstract: This thesis examines the fairness of Automated Machine Learning (AutoML) tools in human resource hiring systems through the combined lenses of regulat

Directed Neuro-Symbolic Stochastic Execution for Verification of Distributed Parallel AI Programs

arXiv:2608.07947v1 Announce Type: new Abstract: Distributed parallel Artificial Intelligence (AI) programs expose reliability gaps that conventional testing cannot close: parallel executions are non-d

Distribution-Free Conformal Prediction for Steel Fatigue Strength: Marginal Validity Is Not Enough

arXiv:2608.07589v1 Announce Type: cross Abstract: Predicting fatigue failure in steel components experimentally is costly because it requires testing across multiple compositions and processing condit

safetyarxiv-cs-lg

DocPure: Prompt-Free Unified Document Restoration via Degradation-Aware Structure-Guided Wavelet Modulation

arXiv:2608.09536v1 Announce Type: new Abstract: High-quality document images are pivotal for information archiving and downstream automatic processing. However, they are frequently compromised by dive

Tutorials

Efficient Test-Time Scaling for LLM-based Time Series Forecasting

arXiv:2608.08675v1 Announce Type: new Abstract: Long-term time series forecasting benefits from preserving global structure such as trends and seasonality. Recent LLM-based forecasters often improve a

tutorialsarxiv-cs-lg

EmoPatient: An Emotion-Directed Patient Simulator for Realistic Palliative Care Communication Training

arXiv:2608.07495v1 Announce Type: cross Abstract: Effective communication during palliative care discussions is a critical clinical skill, yet training clinicians to manage complex patient emotions re

End-to-End Neural Decomposition with Koopman Operators for Time-Series Forecasting

arXiv:2608.08788v1 Announce Type: cross Abstract: Koopman theory offers a linear-operator view of nonlinear sequence dynamics by lifting observations into a space where evolution is governed by a line