Search: “models”

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

Research

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

DGX agent

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

researcharxiv-cs-cv

11 Aug 2026

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

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

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

Entanglement-Free Trajectory Planning for Tethered Mobile Robots with a Slack Tether

arXiv:2608.09860v1 Announce Type: new Abstract: In motion planning algorithms for tethered mobile robots, the entanglement state of the tether is a critical aspect to consider during the planning phas

researcharxiv-cs-ro

Evidence-Grounded Forensic Reasoning for Detecting and Grounding Multi-Modal Media Manipulation

arXiv:2608.08009v1 Announce Type: cross Abstract: Fake news increasingly relies on cross-modal image-text forgeries, making transparent and verifiable reasoning chains an urgent need for Detecting and

Applications

Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems

arXiv:2403.09752v4 Announce Type: replace-cross Abstract: The Internet of Medical Things transcends traditional medical boundaries, enabling a transition from reactive treatment to proactive preventio

applicationsarxiv-cs-ai

Explicit Boundary Markers for Subword Vocabularies

arXiv:2608.08847v1 Announce Type: new Abstract: Subword tokenizers represent many common words twice in space-using writing systems, once with a leading space and once without. The two entries have se

researcharxiv-cs-cl

Exploiting chemical shift variability enables recovery of overlapping metabolites from 1H nuclear magnetic resonance spectra

arXiv:2608.07610v1 Announce Type: cross Abstract: Overlapping peaks and sample-dependent chemical shift variability prevent reliable metabolite recovery from complex biological spectra. This problem i

FailForge: Distilling Procedural Competence from Persistent Failures into Code Agents

arXiv:2608.08570v1 Announce Type: new Abstract: Rejection sampling fine-tuning (RFT) is widely used to train code agents by generating trajectories on verifiable software engineering tasks, retaining

Flow-based conditional cardiac anatomy generation for virtual cohorts

arXiv:2608.09460v1 Announce Type: cross Abstract: Cardiac digital twin research is moving from subject-specific anatomical replicas toward virtual cohorts that represent clinically relevant population

From Alignment to Synthesis Contrastive Volumetric Grounding for Text-to-CT Generation

arXiv:2506.00633v3 Announce Type: replace-cross Abstract: Generating semantically controllable 3D CT volumes from radiology reports requires more than a rich text encoder, it requires vision-language

From @sequoia's own your intelligence event. We're starting to see a new category of company emerge, the Full-Stack AI company, where innova…

From @sequoia's own your intelligence event. We're starting to see a new category of company emerge, the Full-Stack AI company, where innovation happens at both the product and intelligence layer. Tha

safetysonya-huang--x

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks

arXiv:2608.09523v1 Announce Type: new Abstract: Deep neural network (DNN) training with stochastic gradient descent (SGD) and its variants achieves strong empirical performance, yet classical optimiza

GenTrack3: Hybrid Stochastic-Deterministic Online Multi-Object Tracking with Cluster-Aware Association

arXiv:2608.09581v1 Announce Type: new Abstract: Multi-object tracking (MOT) involves maintaining consistent target identities as objects dynamically enter and leave a scene. Deterministic approaches,

High-Capacity Generalized Hopfield Networks

arXiv:2608.08226v1 Announce Type: cross Abstract: Generalized Hopfield networks are introduced where memories and neurons are continuous variables that lie on a Riemannian manifold. We explicitly focu

safetyarxiv-cs-cv

Human-Level Text-to-SQL via Reinforcement Learning on Verified Data, Without Pipeline Engineering

arXiv:2603.20004v3 Announce Type: replace-cross Abstract: Translating natural language questions to SQL queries (Text-to-SQL) is a long-standing problem in database research. Recent efforts have focus

researcharxiv-cs-cl

Local Ai

Label Granularity Skew in Federated Learning with Hierarchical Image Classification

arXiv:2608.09236v1 Announce Type: new Abstract: Federated learning enables privacy-preserving collaboration across distributed devices without centralizing local data. However, clients may differ not

local-aiarxiv-cs-lg

Linearized 2-Simplicial Attention

arXiv:2608.09307v1 Announce Type: new Abstract: We present a linearized form of 2-simplicial attention by rewriting the trilinear score as an inner product between a composite query and a key, so that

Machine Learning and Data Analysis Using Posets: A Survey

arXiv:2404.03082v3 Announce Type: replace Abstract: Partially ordered sets (posets) are discrete mathematical structures that formalize the notion of comparison without forcing every pair of objects t

Matrix Completion via Nonsmooth Regularization of Fully Connected Neural Networks

arXiv:2403.10232v2 Announce Type: replace-cross Abstract: Conventional matrix completion methods approximate the missing values by assuming the matrix to be low-rank, which leads to a linear approxima

Mitigating Gender Bias in English to Romanian Machine Translation

arXiv:2608.08606v1 Announce Type: cross Abstract: Machine translation (MT) systems often fail to correctly translate gender, especially when converting from a gender-neutral language like English to a

ML-Based Hierarchical Prediction for Practical Energy Scheduling in Dynamic NTN-WPT Systems

arXiv:2608.08804v1 Announce Type: cross Abstract: With advancements in long-distance wireless power transfer (WPT) and space-based energy technologies, integrating WPT into non-terrestrial networks (N

neuralGAM: An R Package for Fitting Generalized Additive Neural Networks

arXiv:2505.08610v2 Announce Type: replace-cross Abstract: Nowadays, Neural Networks are considered one of the most effective methods for various tasks such as anomaly detection, computer-aided disease

OccAnyScene: Towards Unified Indoor-Outdoor 3D Occupancy Predictio

arXiv:2608.08696v1 Announce Type: new Abstract: 3D occupancy prediction is fundamental to scene understanding, yet existing 3D semantic occupancy methods are typically specialized to fixed scene types