Search: “papers”

Factorized AdaBoost.MH Achieves the Same Convergence Rate as AdaBoost.MH

arXiv:2608.01091v1 Announce Type: new Abstract: AdaBoost.MH reduces multi-class classification to a collection of binary subproblems and enjoys the classical boosting-type convergence guarantee under

Model Releases

FairForensics: Seeing Expressions and Parsing Demographics via Vision-Language Modeling for Generalizable Fair Deepfake Detection

DGX agent

arXiv:2608.01661v1 Announce Type: new Abstract: The challenge of fair deepfake detection (FDD) has attracted increasing attention. Existing fairness-enhanced detectors often suffer from suboptimal gen

model-releasesarxiv-cs-cv

4 Aug 2026

Fairness in Augmented Graph Learning: A Survey

arXiv:2504.21296v2 Announce Type: replace Abstract: Graph learning has evolved into Augmented Graph Learning (AGL) by integrating specialized machine learning (ML) techniques. Examples include federat

Fast Discovery of Inclusion Dependencies with Desbordante

arXiv:2608.02213v1 Announce Type: cross Abstract: Inclusion dependency is a relation between attributes of tables that indicates possible Primary Key-Foreign Key references. Automatic discovery of inc

Agents

FRA-NBV: A Fast and Reflectivity-Aware Next-Best-View Strategy

arXiv:2608.01950v1 Announce Type: new Abstract: Autonomous 3D reconstruction with depth sensors is strongly affected by reflective surfaces, which cause missing or unreliable measurements and reduce t

agentsarxiv-cs-ro

From Global to Local: A Scalable Benchmark for Local Posterior Sampling

model-releasesarxiv-cs-lg

arXiv:2507.21449v2 Announce Type: replace-cross Abstract: Degeneracy is an inherent feature of the loss landscape of neural networks, but it is not well understood how stochastic gradient MCMC (SGMCMC

From Vessel Trajectories to Safety-Critical Encounter Scenarios: A Generative AI Framework for Autonomous Ship Digital Testing

arXiv:2603.28067v2 Announce Type: replace Abstract: Digital testing has emerged as a key paradigm for the development and verification of autonomous maritime navigation systems, yet the availability o

Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction

arXiv:2608.01202v1 Announce Type: new Abstract: Fruit ripeness prediction (FRP) is a classification-based agricultural computer vision task that has attracted much attention, thanks to its wide-rangin

Gaokerena: A Small Persian Medical Language Model Family

model-releasesarxiv-cs-cl

arXiv:2608.00932v1 Announce Type: new Abstract: The integration of artificial intelligence into medical question-answering systems has advanced rapidly; however, research remains predominantly focused

Generalized Quadratic Gradient: A New Direction in Optimization via the Fusion of Positive-Definite Curvature Matrices and Gradients into A Unified Framework

arXiv:2608.01552v1 Announce Type: cross Abstract: Quadratic Gradient (QG) is a Newton-type optimization framework that bridges first-order gradient descent and second-order optimization by incorporati

local-aiarxiv-cs-lg

Generative Brownian Bridge Diffusion In Motion Space For Enhanced Myocardial Strain Analysis

arXiv:2608.01677v1 Announce Type: new Abstract: Myocardial strain analysis of cardiac magnetic resonance (CMR) images provides an important tool for evaluating cardiac function. However, current techn

tutorialsarxiv-cs-cv

Generative Models for Modeling and Synthesizing MIMO Channels in Adverse Weather Conditions

arXiv:2608.00156v1 Announce Type: cross Abstract: The push for broader coverage in future cellular networks depends on reliable service, yet this is increasingly harder to do as we encounter more inst

Gram-Space: Structure-Preserving Codebook Compression for Memory-Efficient Neuro-Symbolic AI

model-releasesarxiv-cs-lg

arXiv:2608.01528v1 Announce Type: new Abstract: Vector symbolic architectures (VSA) are widely used for reasoning in neuro-symbolic (NeSy) AI, yet high-dimensional codebooks often create severe memory

Grounded Vision-Language Interpreter for Long-Horizon Bimanual Task and Motion Planning

arXiv:2506.03270v3 Announce Type: replace Abstract: While recent advances in vision-language models have accelerated language-guided robot planning, their black-box nature lacks the safety guarantees

safetyarxiv-cs-ro

Hardware

HetRoute Heterogeneous and Cost-aware Collaborative Routing Framework for Distributed Edge MoE Inference

arXiv:2608.00577v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models have become a dominant architecture for large-scale AI services, yet deploying them over geo-distributed heterogeneous

hardwarearxiv-cs-cl

Hybrid-Domain Posterior Sampling for Inverse Problems via Latent Flow Matching

arXiv:2608.00537v1 Announce Type: new Abstract: Latent Flow Models have revolutionized compressed-space image synthesis, yet their application to high-fidelity inverse problems remains bottlenecked. I

safetyarxiv-cs-cv

InstancePin: Instance-Addressable Layout-to-Image Diffusion via Coordinate Pinning

arXiv:2608.00588v1 Announce Type: new Abstract: Layout-to-image diffusion models have achieved impressive semantic controllability by conditioning generation on category-level segmentation maps. Howev

Interaction Dynamics MPC for Knee Rehabilitation Exoskeletons: A Closed-Loop SEA Outer-Loop Study

arXiv:2606.13485v3 Announce Type: replace-cross Abstract: Safe rehabilitation is an interaction-dynamics problem: the controller must regulate a prescribed motion while absorbing involuntary spasm, vo

safetyarxiv-cs-ro

Agents

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving

arXiv:2512.10739v3 Announce Type: replace Abstract: Large Reasoning Models (LRMs) have expanded the mathematical reasoning frontier through Chain-of-Thought (CoT) techniques and Reinforcement Learning

agentsarxiv-cs-cl

Latent-Regime Bias Auditing for Volatility Forecasting

arXiv:2608.01599v1 Announce Type: new Abstract: Volatility forecasts are commonly evaluated with aggregate accuracy metrics such as RMSE and MAE, but these metrics can hide conditional failures that m

LAYA: Layer-wise Attention Aggregation for Interpretable Depth-Aware Neural Networks

arXiv:2511.12723v2 Announce Type: replace Abstract: Deep neural networks typically rely on the representation produced by their final hidden layer to make predictions, implicitly assuming that this si

Learning Smooth SE(3) Trajectories under Left-Invariant Riemannian Metrics

arXiv:2608.01562v1 Announce Type: new Abstract: Optimal trajectory generation for rigid-body motions on Lie groups can be formulated as a variational problem that minimizes energy functionals defined

tutorialsarxiv-cs-ro

Learning to Tessellate: Point Cloud Generation via Recursive Spectral Partitioning

arXiv:2608.02432v1 Announce Type: new Abstract: Autoregressive models have emerged as an effective paradigm for point cloud generation. However, most existing approaches rely on heuristic tokenization

Linear Multi-Timescale Retention as a Memory-Efficient Vision-Language Bridge

arXiv:2608.01614v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face a critical computational bottleneck when processing high-resolution imagery due to the O(N^2) memory complexity of So

LOCUS-DT: Localization via Observation-Conditioned Uncertainty Scoring with Digital Twins

arXiv:2608.00406v1 Announce Type: cross Abstract: Accurate indoor localization is essential for emerging applications in robotic navigation and search and rescue. While classical methods typically foc

local-aiarxiv-cs-lg

Loggia dei Lanzi: AI Thermography Enhancement Comparisons through 3D Photogrammetry

arXiv:2608.02404v1 Announce Type: new Abstract: The Loggia dei Lanzi in the Piazza della Signoria is one of Florence's most prominent structures visited by millions every year. Its construction histor

Logit-Origin Centering for Singleton Test-Time Adaptation

arXiv:2608.01074v1 Announce Type: cross Abstract: Tabular data is used extensively in many real-world use cases. Deep learning models have been developed to deal with tabular data, but generally perfo

Logographic Character Visual Pretraining via Semantic-based Contrastive Learning

arXiv:2608.00096v1 Announce Type: new Abstract: Current deep learning-based character vision studies, e.g., text recognition, character image denoising, and historical text completion, are offering ne

MA-HEAD-Net: Adaptive Rule-Guided Multi-Agent DRL for AoI Minimization in UAV-Assisted Emergency Networks

arXiv:2608.01128v1 Announce Type: cross Abstract: In post-disaster scenarios, unmanned aerial vehicles (UAVs) are critical for establishing emergency communication networks. For time-critical rescue m

MBO Scheme for Local Chan--Vese Segmentation

arXiv:2608.00893v1 Announce Type: new Abstract: Robust to intensity inhomogeneity, the local Chan--Vese (LCV) model extends the classical Chan--Vese (CV) image segmentation method by incorporating loc

local-aiarxiv-cs-cv

MDWD: A Street-Level Dataset for Municipal Solid Waste Detection in Dense Urban Environments

arXiv:2608.00257v1 Announce Type: new Abstract: Automated visual monitoring of urban environments is a growing Computer Vision research area, but municipal solid waste detection remains under-represen

Motion Planning for Mobile Manipulators Navigating Doorways via Model Predictive Control

arXiv:2608.00206v1 Announce Type: new Abstract: Navigating doorways is a fundamental capability for mobile manipulators operating in human environments, requiring coordinated motion between the mobile

researcharxiv-cs-ro

Neural Born Series Operator for Biomedical Ultrasound Computed Tomography

arXiv:2312.15575v2 Announce Type: replace-cross Abstract: Ultrasound Computed Tomography (USCT) provides a radiation-free option for high-resolution clinical imaging. Despite its potential, the comput

NISF++: Geometrically-grounded implicit representations of 3D+time cardiac function from 2D short- and long-axis MR views

arXiv:2608.00752v1 Announce Type: new Abstract: Clinical acquisition in cardiac magnetic resonance (CMR) imaging involves obtaining cross-sectional planes of the heart along the radial and longitudina

safetyarxiv-cs-cv

Open-DiffLoco: Open-Source Differentiable Learning for Deployable Blind Quadruped Locomotion

arXiv:2608.02069v1 Announce Type: cross Abstract: Developing deployable locomotion policies through conventional reinforcement learning often requires complex reward engineering and expensive training

local-aiarxiv-cs-lg

OSSDD - a New Open Dataset for Sentinel-1 Ship Detection

arXiv:2608.01963v1 Announce Type: new Abstract: Ship detection in Synthetic Aperture Radar (SAR) images plays an important role for maritime situational awareness, especially with respect to different

Partially-Observable Transmission Control for UAV-Enabled Federated Learning in IoT Networks

arXiv:2608.00855v1 Announce Type: cross Abstract: Uncrewed aerial vehicle (UAV)-enabled federated learning (FL) can provide flexible, on-demand edge intelligence for large-scale IoT deployments, but o

PeCA: Palette Context Assisted Inference for Test-Time Paint-Bucket Colourisation on Animation Videos

arXiv:2608.00903v1 Announce Type: new Abstract: In animation production, paint-bucket colourisation for hand-drawn animation is a labour-intensive procedure that assigns each enclosed region in line s

Pixel Ignores, Superpixel Sees: Adverse Weather Image Restoration via Semantic-Center SSM

arXiv:2608.01760v1 Announce Type: new Abstract: Adverse weather image restoration aims to recover clear visibility from degraded images in complex weather conditions. Existing works attempt to address

PixelSR: Efficient Screen Content Super-Resolution via Pixel Classification

arXiv:2608.00646v1 Announce Type: new Abstract: Screen content images are generally composed of texts and graphics. Compared to natural images, these man-made images contain a large quantity of sharp

local-aiarxiv-cs-cv

Plasticity of Growing and Elastic Neural Networks in Online Continual Learning

arXiv:2608.01475v1 Announce Type: new Abstract: Neural networks that can grow or both grow and shrink during learning, referred to as growing neural networks and elastic neural networks, respectively,

tutorialsarxiv-cs-lg

PolymerGPT: Multi-property Optimization with a Decoder-Based GPT Model for Generative Polymer Design

arXiv:2608.01431v1 Announce Type: cross Abstract: Polymer property prediction and inverse generative design targeting desired properties are two crucial tasks in machine learning-assisted polymer desi

Probing the 3D Object-Level Understanding of Pre-Trained Detection Transformers

arXiv:2608.01495v1 Announce Type: new Abstract: Detection transformer models, including DETR and its extensions, learn to output a set of object-level embeddings that can be simultaneously decoded int

tutorialsarxiv-cs-cv

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection

arXiv:2608.01348v1 Announce Type: new Abstract: Data augmentation, which simulates diverse visual variations to expand the source distribution and induce synthetic domain shifts, is a simple yet effec

Protocol generalisation for brain tissue microstructure estimation via hypernetwork-controlled geometric deep learning

arXiv:2608.02053v1 Announce Type: cross Abstract: Brain tissue microstructure estimation with machine learning provides higher computational efficiency than conventional fitting. However, machine lear

Pruned BPE: Post-training Visibility Pruning and Token Reallocation for Byte Pair Encoding

arXiv:2608.00837v1 Announce Type: new Abstract: Byte Pair Encoding (BPE) is widely used for subword tokenization, but standard BPE exposes every learned merge token to the downstream model, including

researcharxiv-cs-cl

Push-Wiper: Toward General-Purpose Robotic Cleaning across Varied Stains and Surfaces with Segmented Pushing Trajectories

arXiv:2608.00730v1 Announce Type: new Abstract: Viscous stains, characterized by high viscosity and complex rheological properties, remain a major challenge for robotic surface cleaning. Conventional

safetyarxiv-cs-ro

PyDPF: A Python Package for Differentiable Particle Filtering

arXiv:2510.25693v3 Announce Type: replace-cross Abstract: State-space models (SSMs) are a widely used tool in time series analysis. In the complex systems that arise from real-world data, it is common

applicationsarxiv-cs-lg