Search: “papers”

ToW3D: Consistency-aware Interactive Point-based Mesh Editing on GANs

arXiv:2609.26078v1 Announce Type: new Abstract: In this paper, we propose ToW3D that enables precise and consistent control over 3D generative adversarial networks (GANs) with the Tug-of-War competiti

researcharxiv-cs-cv

23 Sept 2026

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A multi-temporal dataset for mapping burned areas in the Brazilian Cerrado using time series of remote sensing imagery

DGX agent

arXiv:2609.23687v1 Announce Type: cross Abstract: This paper introduces a multi-temporal tabular dataset derived from satellite images to map burned areas in the Chapada dos Veadeiros National Park, i

researcharxiv-cs-cv

22 Sept 2026

Agents

A Tutorial on Prompt Engineering: From Messy Thoughts to AI Workflows

arXiv:2609.22249v1 Announce Type: new Abstract: This paper treats prompt engineering as a discipline for turning informal human intent into structured AI work specifications. It develops the practice

agentsarxiv-cs-cl

Balancing Reasoning and Hardware Constraints in RAG Pipelines for Ukrainian Multi-Domain Document Understanding

model-releasesarxiv-cs-cl

arXiv:2609.22124v1 Announce Type: new Abstract: This paper describes the system submitted to the UNLP 2026 Shared Task on Multi-Domain Document Understanding. The challenge required extracting precise

Beyond the Survey: A Systematic Empirical Study of Detection and Association in Visual MOT

arXiv:2609.22291v1 Announce Type: new Abstract: This paper presents a comprehensive experimental evaluation and detailed analysis of state-of-the-art multi-object tracking algorithms, with an emphasis

researcharxiv-cs-cv

Conformalized Quantile Regression and Minimax Limits of Fixed-Score Calibration under Known Covariate Shift

arXiv:2609.24929v1 Announce Type: cross Abstract: In this paper, we study nonasymptotic L^p error bounds for interval length and conditional coverage in split conformalized quantile regression (CQR).

ERUPT: An Open Toolkit for Interfacing with Robot Motion Planners in Extended Reality

arXiv:2510.02464v2 Announce Type: replace Abstract: We present the Extended Reality Universal Planning Toolkit (ERUPT), an extended reality (XR) system for interactive motion planning. This paper serv

applicationsarxiv-cs-ro

Explainable Neuro-Fuzzy Prediction for Trustworthy Decision-Making in Maritime

model-releasesarxiv-cs-lg

arXiv:2609.24358v1 Announce Type: new Abstract: Predicting when maritime systems require maintenance can be critical, avoiding hazards and costly consequences. To address this problem, this paper prop

Fast Graph Laplacian Estimation using Effective Resistance

arXiv:2609.23668v1 Announce Type: cross Abstract: Inferring network topology from noisy node observations is a central problem in graph signal processing. In this paper, we consider Laplacian-constrai

From Outliers to Topics in Language Models: Anticipating Trends in News Corpora

arXiv:2509.22030v2 Announce Type: replace Abstract: This paper examines how outliers, often dismissed as noise in topic modeling, can act as weak signals of emerging topics in dynamic news corpora. Us

Tutorials

InterHier: Learning Interconnected Hierarchical Semantics for Open-Vocabulary Object Detection

arXiv:2609.24026v1 Announce Type: new Abstract: In this paper, we investigate the limitations of fixed, hand-crafted connectors in hierarchical semantic representations for open-vocabulary object dete

tutorialsarxiv-cs-cv

Layered e-skin for Shear Sensing

arXiv:2609.22493v1 Announce Type: new Abstract: This paper presents a stacked two-layer force-sensing resistor (FSR) array designed for robotic fingertips that combines high-resolution pressure mappin

researcharxiv-cs-ro

Learning-Based 3D Reconstruction of Power Networks from Aerial Point Clouds

arXiv:2609.23915v1 Announce Type: cross Abstract: This paper presents an end-to-end framework for reconstructing overhead power utility network topology and extracting span-level physical metadata fro

applicationsarxiv-cs-cv

Monocultural Biases: Correlated biases in large language models lead to unequal systemic exclusion rates in hiring

arXiv:2609.22169v1 Announce Type: new Abstract: Employers are increasingly using large language models (LLMs) to automate their hiring process. This paper investigates the risk of monocultural biases,

Multivariate quantile regression via Kolmogorov-Arnold Networks

arXiv:2609.23906v1 Announce Type: new Abstract: This paper introduces a novel algorithm for predicting conditional joint distributions of vector-valued targets in stochastic systems whose randomness i

Observational Equivalence of LLM and Human Annotation

arXiv:2609.22133v1 Announce Type: new Abstract: In this paper, we show that LLM and human coding are observationally equivalent in terms of annotation quality: recent LLMs agree with expert coders at

Partial-Scan-and-Move Source Seeking for Mobile Robots

arXiv:2609.23786v1 Announce Type: cross Abstract: This paper presents a partial-scan-and-move strategy for source seeking with a mobile robot equipped with an offset scalar sensor. At each robot posit

researcharxiv-cs-ro

Rapidly-Iterating Grid-Based Near-Optimal Kinodynamic Motion Planning

arXiv:2609.22733v1 Announce Type: new Abstract: This paper develops the Rapidly-iterating kinoDynamic Grid (RDG) algorithm, an asymptotically near-optimal kinodynamic motion planning algorithm that pr

safetyarxiv-cs-ro

RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent

model-releasesarxiv-cs-lg

arXiv:2502.07977v3 Announce Type: replace Abstract: Empirical risk minimization (ERM) is a cornerstone of modern machine learning. This paper focuses on the man-in-the-middle (MITM) attack, wherein ad

SKstars at SHROOM: Visions Agreement-Guided Ensembling of Zero-Shot and LoRA-Adapted Vision--Language Models

arXiv:2609.24198v1 Announce Type: cross Abstract: This paper describes the SKstars submission to SHROOM-Visions 2026, a shared task on fine-grained hallucination detection in large vision-language mod

researcharxiv-cs-cv

Small Gradient Norm Regret for Online Convex Optimization

arXiv:2601.13519v4 Announce Type: replace-cross Abstract: This paper introduces a new problem-dependent regret measure for online convex optimization with smooth losses. The notion, which we call the

Stagewise Anomaly Detection for E-Transaxle Quality Monitoring Using Wavelet and STFT Features

arXiv:2609.22172v1 Announce Type: cross Abstract: This paper presents two interpretable machine-learning frameworks for quality screening of e-transaxle assemblies in electric vehicles: a Stagewise Wa

applicationsarxiv-cs-lg

Statistical Inference for Adversarial Training: Central Limit Theorems via Optimal Transport

arXiv:2609.22240v1 Announce Type: new Abstract: The purpose of this paper is to rigorously quantify the statistical and learning-theoretic properties of adversarial training models for classification.

Hardware

Streaming Video Editing with Easy Adaptation

arXiv:2609.24788v1 Announce Type: new Abstract: In this paper, we propose SVEET, a framework that requires merely training on a pretrained bidirectional video diffusion model but supports high-quality

hardwarearxiv-cs-cv

TEMPER: Temporal Encoder-Masked Probabilistic Ensemble Regressor for Time-Series Forecasting

arXiv:2609.23701v1 Announce Type: cross Abstract: Probabilistic forecasting requires accurate central predictions and calibrated uncertainty estimates. This paper presents TEMPER, the Temporal Encoder

Towards Robust Classroom Attendance: A Comprehensive Evaluation of Face Detection and Recognition Models

model-releasesarxiv-cs-cv

arXiv:2609.22750v1 Announce Type: new Abstract: Manual attendance methods, such as paper or register-based systems, take a lot of time, can lead to errors, and are easy to falsify. Face recognition is

Transfer Learning for Matrix Completion

arXiv:2507.02248v2 Announce Type: replace-cross Abstract: In this paper, we explore the knowledge transfer under the setting of matrix completion, which aims to enhance the estimation of a low-rank ta

Local Ai

XSQ-AST: An Explainable Audio Spectrogram Transformer Framework for Localising Synthetic Speech Artifacts

arXiv:2609.24770v1 Announce Type: cross Abstract: Localising artifacts in synthetic speech remains challenging, as most evaluation methods yield only global quality scores. This paper presents XSQ-AST

local-aiarxiv-cs-lg

4DGS-Fixer: Generative Sparse-View 4D Gaussian Splatting with Iterative Refinement Guided by Video Diffusion Priors

model-releasesarxiv-cs-cv

arXiv:2609.21176v1 Announce Type: new Abstract: This paper addresses the challenges of dynamic scene synthesis from sparse-view videos. Existing methods employ geometric priors, adaptive optimization,

Local Ai

Adapting Rigid-Body Dynamics Derivatives for Constraint Embedding Closed-Chain Models

arXiv:2609.21024v1 Announce Type: new Abstract: This paper extends an existing algorithm for the first-order derivatives of rigid-body dynamics to the case of closed-chain kinematic systems modeled us

local-aiarxiv-cs-ro

Adaptive Uncertainty-Aware Modeling and Stochastic Radial Basis Function Predictive Control for Personalized Fluid Resuscitation

arXiv:2609.21821v1 Announce Type: cross Abstract: This paper presents a novel framework integrating Bayesian physiological modeling with optimal control strategies to achieve uncertainty-aware, person

MicroHookACT: Monocular Microscopic Vision Guided Visuomotor Policy for Flexible Microelectrode Hooking

arXiv:2609.21365v1 Announce Type: new Abstract: Automated needle-loop hooking is a critical step in flexible microelectrode (FME) implantation. This paper presents MicroHookACT, an imitation learning-

safetyarxiv-cs-ro

ProTracer: Proprioception-Guided Failure Diagnosis in Robot Manipulation

model-releasesarxiv-cs-cv

arXiv:2609.21369v1 Announce Type: cross Abstract: This paper presents a comprehensive framework for robot manipulation failure analysis that includes binary failure detection, failure categorization,

Reinforcement Learning under External Influence: Guarantees, Algorithms, and Sample Complexity

arXiv:2305.16056v5 Announce Type: replace-cross Abstract: In this paper, we study the problem of reinforcement learning under the influence of external events. For this, we consider Markov decision pr

safetyarxiv-cs-ai

Agents

SkillIR: Evolving Scene-Aware Skills for Agentic Image Restoration

arXiv:2609.21468v1 Announce Type: new Abstract: This paper studies agentic image restoration, in which multimodal agents coordinate specialized restoration tools to recover images affected by complex

agentsarxiv-cs-cv

Tutorials

TRACE: Coverage Path Planning for Unknown Environments Using Hierarchical Coverage Tree

arXiv:2609.21777v1 Announce Type: new Abstract: This paper presents a novel online coverage path planning (CPP) algorithm, called TRACE, for real-time coverage of unknown environments. TRACE is built

tutorialsarxiv-cs-ro

Local Ai

Transsion's Speaker-Attributed Multilingual ASR System for the MLC-SLM 2026 Challenge

arXiv:2609.20833v1 Announce Type: new Abstract: This paper presents the Transsion Speech Team submission to Task 1 of the MLC-SLM 2026 Challenge, which focuses on speaker-attributed transcription for

local-aiarxiv-cs-cl

A Phonemically Comprehensive, ASCII-Only Romanization Scheme for Thai and Lao: Systematic Cross-Lingual Correspondence and Chinese-User-Friendly Design

arXiv:2609.19736v1 Announce Type: new Abstract: This paper proposes a phonemically comprehensive, ASCII-only romanization scheme for Thai and Lao, treating the two closely related languages as a unifi

Advantage Scale Calibration Imbalance in Group-Relative Optimization under Low-Variance Rewards: Diagnosis and Bounded Recovery

arXiv:2609.19164v1 Announce Type: new Abstract: In verifier-style RLVR, group-relative optimization often treats advantage scale as an implementation detail. This paper separates two low-variance case

COIN-GP: Cooperative Online Learning in Networked Distributed Systems with Partial Measurements via Gaussian Process Regression

arXiv:2609.20598v1 Announce Type: new Abstract: In this paper, we tackle the problem of jointly estimating the system states and partially unknown dynamics within distributed sensor-equipped networks,

Demystifying Linear Operator Learning for Control Systems

arXiv:2609.19428v1 Announce Type: cross Abstract: This paper proposes a structured approach to learning linear operators for control systems from data. We address both structural and learning-theoreti

Agents

Distributed Event-Triggered Distance-Based Formation Control for Multi-Agent Systems

arXiv:2509.12390v3 Announce Type: replace Abstract: This paper addresses collaborative formation control for multi-agent systems with limited resources. We consider a team of robots tasked with achiev

agentsarxiv-cs-ro

DR-MPC: Fast and Feasible Dynamics-Relaxed Model-Predictive Control for Legged Locomotion

arXiv:2609.20035v1 Announce Type: new Abstract: This paper presents dynamics-relaxed model predictive control (DR-MPC), a novel MPC formulation for legged locomotion, and a tailored interior-point met

researcharxiv-cs-ro

Dynamic-LIVO: A Dynamic-Aware LiDAR-Inertial-Visual Odometry System Using Spatio-Temporal Normals

model-releasesarxiv-cs-ro

arXiv:2609.19336v1 Announce Type: new Abstract: This paper proposes Dynamic-LIVO, a dynamic-aware LiDAR-Inertial-Visual Odometry (LIVO) system for robust state estimation and static colored mapping in

DynaWeightPnP: Toward global real-time 3D-2D solver in PnP without correspondences

arXiv:2409.18457v2 Announce Type: replace Abstract: This paper addresses a special Perspective-n-Point (PnP) problem: estimating the optimal pose to align 3D and 2D shapes in real-time without corresp

safetyarxiv-cs-cv

Layer-wise Curriculum Learning for Efficient LLM Compression

model-releasesarxiv-cs-ai

arXiv:2609.19213v1 Announce Type: cross Abstract: In this paper, we introduce layer-wise curriculum learning for efficient LLM compression. The proposed method facilitates the knowledge transfer from

Marginal utility, matrix factorization, and the Key-Value (KV) cache: a unified information-economic framework for sovereign geo-mining inference

model-releasesarxiv-cs-ai

arXiv:2609.20068v1 Announce Type: new Abstract: This paper builds a theoretical bridge between the economic notion of marginal utility and two machine-learning constructs, matrix factorization and the

PART: Learning 3D Part Assembly and Retrieval with Transformers

arXiv:2609.19872v1 Announce Type: new Abstract: 3D assembly is fundamental to modern manufacturing and digital content creation. In this paper, we present PART, a unified transformer-based framework f

applicationsarxiv-cs-cv