Search: “research”

WISE-ATTA: When to Ask for Labels in Budgeted Active Test-Time Adaptation

arXiv:2609.37687v1 Announce Type: new Abstract: Active test-time adaptation (ATTA) improves robustness under distribution shift by updating a deployed model during inference while selectively querying

researcharxiv-cs-ai

30 Sept 2026

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WUSH-KV: KV Cache Quantization with Data-Adaptive Transforms

DGX agent

arXiv:2609.38121v1 Announce Type: new Abstract: KV cache memory and bandwidth costs grow with context length and batch size, which limits efficient long-context inference. To address this bottleneck,

researcharxiv-cs-lg

30 Sept 2026

Xiaomi-OCR-0 Technical Report

arXiv:2609.36136v1 Announce Type: new Abstract: Compact OCR-specific vision-language models achieve strong document parsing performance, but often rely on costly supervision and focus primarily on vis

30 Sept 2026

Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression

arXiv:2602.02848v2 Announce Type: replace Abstract: Advances in large language models have driven strong performance across many tasks, but their memory and compute costs still hinder deployment. SVD-

30 Sept 2026

A Comparative Transfer-Learning Study of CNN Backbones for Partial Face Recognition on the SoF Dataset

arXiv:2609.31677v1 Announce Type: new Abstract: Face recognition is widely deployed in surveillance, access control, and forensic workflows, yet accuracy degrades sharply once the face is occluded by

A Computer Vision Approach to Visual Fraud Detection in Phishing Websites Using YOLOv8

arXiv:2609.34015v1 Announce Type: cross Abstract: Phishing remains one of the most common vectors for financial and identity fraud, and most detection systems still rely on inspecting a page's URL, HT

A Disk-Shaped Magnetoelastic Torque Sensor for Robotic Joints Using Permanent Magnetization

arXiv:2609.33542v1 Announce Type: new Abstract: Direct torque sensing is a growing need in the robotics community to enable precise control and interactions where torque estimation from motor current

researcharxiv-cs-ro

A Hierarchy of Entropy-Shapley Games for Multivariate Predictive Uncertainty

arXiv:2609.35217v1 Announce Type: cross Abstract: Modern probabilistic machine learning models increasingly produce multivariate outputs with complex dependence structure, from multi-step time-series

A Kernel-based Stochastic Approximation Framework for Nonlinear Operator Learning

arXiv:2509.11070v4 Announce Type: replace-cross Abstract: We develop a stochastic approximation framework for learning nonlinear operators between infinite-dimensional spaces utilizing general Mercer

A Multimodal Autonomic Sensing Framework for Objective Assessment of Patient Responses to Dental Pulp Stimulation

arXiv:2609.35121v1 Announce Type: new Abstract: Patient responses to dental pulp testing, ranging from no sensation to intense pain, provide important information for assessing pulp status in endodont

A Multimodal Feature Distillation with Mamba-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities

arXiv:2404.14019v3 Announce Type: replace Abstract: Existing brain tumor segmentation methods usually utilize multiple Magnetic Resonance Imaging (MRI) modalities in brain tumor images for segmentatio

A Novel Unified Approach to Deepfake Detection

arXiv:2601.03382v2 Announce Type: replace Abstract: Advancements in the field of AI are increasingly giving rise to various threats, one of the most prominent being the synthesis and misuse of deepfak

A Spectral Theory of Compositional Learning

arXiv:2609.33708v1 Announce Type: new Abstract: How does compositional reasoning emerge during learning? We address this question by mathematically analyzing the learning dynamics of deep linear netwo

A Statistical Perspective on Knowledge Distillation: Foundations, Classical Methods, and Large Language Model Extensions

arXiv:2609.33727v1 Announce Type: cross Abstract: Knowledge Distillation (KD) has emerged as a vital paradigm for transferring the capabilities of high-capacity models to efficient ``student'' counter

A Unified Uncertainty Representation for Graph Neural Networks via Doubly-Spectral Stochastic Expansion

arXiv:2609.35703v1 Announce Type: new Abstract: Reliable deployment of graph neural networks requires calibration, out-of-distribution (OOD) detection, and robustness to distribution shift, yet existi

A Unifying Framework of Concept-based Explainable AI with Completeness Guarantees

arXiv:2609.34750v1 Announce Type: cross Abstract: Concept-based explanations describe neural network predictions through human-understandable properties of inputs called concepts. The field encompasse

A Visual Classification Dataset and Model Evaluation for Historical Manuscript Illustrations

arXiv:2609.33449v1 Announce Type: new Abstract: Historical manuscript illustrations preserve rich visual evidence of past cultures. They depict people, animals, plants, diagrams, music notations, and

ABO-Med: Accelerated Bilevel Optimization for Few-Shot Medical Image Classification

arXiv:2609.33176v1 Announce Type: new Abstract: In recent years, bilevel optimization has been widely used in a variety of machine learning tasks. However, prior bilevel optimization algorithms genera

Accurate Sampling from Diffusion Models

arXiv:2609.29902v1 Announce Type: cross Abstract: A new proposal called DM-SMC (Diffusion Model - Sequential Monte Carlo) is investigated, which samples ensembles defined in terms of an action, using

ACPruner: Visual Token Pruning as Biased Attention Coverage Maximization in LVLMs

arXiv:2609.34558v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) face significant computational inefficiencies caused by the large number of visual tokens. Existing visual token pr

Action Sequence Transfer via LLMs for Heterogeneous Environments

arXiv:2609.34730v1 Announce Type: new Abstract: We present an action sequence transfer system that adaptively transfers user action sequences across different target spaces. Given an input action sequ

researcharxiv-cs-ro

Adapting neural operators for mechanics decisions under changing operating conditions

arXiv:2609.33978v1 Announce Type: cross Abstract: Neural operators can accelerate repeated nonlinear mechanics calculations, but their accuracy can deteriorate as operating conditions move beyond the

Adaptive Latent Capacity for World Models

arXiv:2609.32921v1 Announce Type: new Abstract: We introduce Adaptive LeWorldModel (ALeWM), a world model based on a joint-embedding predictive architecture (JEPA) that learns to concentrate predictiv

Adjoint-based shape optimization of a ship hull using a Conditional Variational Autoencoder (CVAE) assisted propulsion surrogate model

arXiv:2602.14907v3 Announce Type: replace-cross Abstract: Adjoint-based shape optimization of ship hulls is a powerful tool for addressing high-dimensional design problems in naval architecture, parti

Admissible Diffusion for Multimodal Interventional Trajectories

arXiv:2609.34433v1 Announce Type: new Abstract: Generating a plausible clinical trajectory does not establish what would happen under a different treatment. We present ADMIT, a framework combining irr

Advancing Video-Text Pretraining with Multi-View Captions

arXiv:2609.35090v1 Announce Type: new Abstract: Video-text pretraining has achieved remarkable progress through the scaling of models and datasets, yet the quality of language supervision remains unde

Advancing Wildlife Conservation through Multimodal Animal Re-Identification with Environmental Metadata

arXiv:2609.34094v1 Announce Type: new Abstract: Identifying individual animals is crucial for effective wildlife monitoring and conservation efforts. Recent advancements in computer vision have shown

AECSF: Adaptive Ensemble Conditional Score Filtering for High-Dimensional Nonlinear Data Assimilation

arXiv:2609.32411v1 Announce Type: cross Abstract: Bayesian state estimation for high-dimensional nonlinear dynamical systems entails a fundamental tension between statistical fidelity and computationa

AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling

arXiv:2605.05586v2 Announce Type: replace Abstract: High-fidelity CFD is essential for aerodynamic design, but repeated simulations are computationally expensive, motivating surrogate models for rapid

Affine Geometry of Gaussian ReLU Networks via Conditional Kac-Rice Formulas

arXiv:2609.32695v1 Announce Type: cross Abstract: We study how the affine geometry of finite ReLU networks is created at random initialization and reorganized by supervised training. We call a sign-ch

AG-CoT: Verified Algorithmic Traces for LLM Program Synthesis on Clifford Circuits

arXiv:2609.33192v1 Announce Type: new Abstract: Scientific code generation can produce executable programs that fail to compute the intended scientific object. We study this problem in language-model

Age-Adaptive Handwriting Reconstruction from an IMU-Based Digital Pen through Shared Representations and Domain-Specific Heads

arXiv:2609.31666v1 Announce Type: cross Abstract: Digital pens are widely used to capture handwriting on digital devices, enabling precise trace recording and enhancing human-computer interaction. How

AGILE-GS: Anchor-Guided Fast Next-Best-View Selection for Active 3D Gaussian Splatting

arXiv:2609.34176v1 Announce Type: new Abstract: Radiance fields need hundreds of views, and their placement matters as much as their number. Next-best-view (NBV) selection for 3D Gaussian Splatting (3

AHMAD: Adaptive Hybrid Multi-task Vision Learning with Assisted Distillation for Keypoint Detection

arXiv:2609.35490v1 Announce Type: new Abstract: Generalist multitasking vision models aim to unify multiple vision tasks within a single framework, enabling more efficient and versatile learning. Howe

Algorithmic Harms Associated with Generative Model-Augmented Recommendation Systems

arXiv:2609.33073v1 Announce Type: new Abstract: In this work, we consider algorithmic harms that may arise as generative models are incorporated into machine learning platforms. We argue that existing

All-Atom GPCR-Ligand Dynamics Simulation via a Residual Latent Flow Mode

arXiv:2602.03902v2 Announce Type: replace-cross Abstract: G-protein-coupled receptors (GPCRs), which are targeted by over one-third of approved drugs, undergo intricate conformational transitions to t

AMBIT: Anticipatory Multimodal Body Recruitment for Bimanual Tracking on a Humanoid

arXiv:2609.33484v1 Announce Type: new Abstract: A humanoid with 5-DoF arms cannot track generic bimanual end-effector trajectories with its arms alone; pelvis and waist motion must be recruited, but w

researcharxiv-cs-ro

An Active-Bottleneck Mechanism for Weak-to-Strong Generalization

arXiv:2609.33835v1 Announce Type: cross Abstract: Weak-to-strong generalization (W2SG) occurs when a student trained on a teacher's predictions outperforms that teacher. We study when this happens und

An Efficient Subspace Algorithm for Federated Learning on Heterogeneous Data

arXiv:2509.05213v2 Announce Type: replace Abstract: This work addresses the key challenges of applying federated learning to large-scale deep neural networks, particularly the issue of client drift du

An End-to-End Latent-Rollout Approach for Pushing Few-Step ImageNet-256 Generation to FID 1.11 without Frechet Losses

arXiv:2609.32376v1 Announce Type: new Abstract: Iterative generation poses a joint optimization problem across steps, as intermediate predictions shape subsequent computations and ultimately determine

An integrated geometric quantification and shape analysis framework for axillary lymph node metastasis in breast cancer patients

arXiv:2609.35437v1 Announce Type: cross Abstract: Quantitative characterization of lymph node morphology is important for assessing axillary lymph node metastasis in breast cancer. However, surfaces r

ANaLOG: Anisotropic Native-Latent Operator Guidance for Solving Inverse Problems

arXiv:2609.31933v1 Announce Type: cross Abstract: Native-latent guidance is a recent paradigm for solving inverse problems with latent diffusion models. It replaces repeated evaluations of the image-s

Anatomy-Structured Hierarchical MIL for Weakly-Supervised Thoracic Disease Detection in Chest X-rays

arXiv:2609.33520v1 Announce Type: new Abstract: Weakly-supervised thoracic disease detection in chest X-rays (CXR) is challenging due to subtle appearances and complex anatomical overlap, motivating a

AquaBEV-Nav: Learned BEV Occupancy for Underwater Navigation and Exploration

arXiv:2609.32156v1 Announce Type: cross Abstract: Safe underwater exploration requires a robot to understand where surrounding structures are located and which regions are available for motion. Existi

Arbitrary-Accuracy Neural Approximation with Optimal Neuron Count and Near-Optimal Bit Complexity

arXiv:2609.35628v1 Announce Type: new Abstract: We study the minimum number of hidden neurons required for arbitrary-accuracy approximation of multivariate Holder-continuous functions on [0,1]^d and t

Architecture-aware Robustness Evaluation of Explainable Deep Learning for Breast Cancer Diagnosis

arXiv:2609.31692v1 Announce Type: new Abstract: Explainable Artificial Intelligence (XAI) has become essential in medical image analysis to ensure transparency of deep learning (DL)-based diagnostic s

Artificial Intelligence Across the Cardiac Amyloidosis Diagnostic and Management Pathway: From Single-Modality Detection to Multimodal Clinical Integration

arXiv:2607.09948v2 Announce Type: replace-cross Abstract: Cardiac amyloidosis (CA) is increasingly recognized but remains substantially underdiagnosed because its clinical and imaging phenotype overla

Artificial Neural Network Assisted Modelling of Tangent Galvanometer Measurements for the Determination of Horizontal Component of Earth's Magnetic Field

arXiv:2609.31930v1 Announce Type: cross Abstract: The Tangent Galvanometer (TG) is a standard undergraduate laboratory experiment for estimating the horizontal component of Earth's magnetic field (BH)