Data Collection

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1 papers in the last 28 days · 0.0% of indexed attention

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Period ending 2026-09-14

1 new paper

A weekly snapshot of new work published in Data Collection.

Period ending 2026-09-07

1 new paper

A weekly snapshot of new work published in Data Collection.

32 papers

Latest in Data Collection

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Using Automated Vehicles Operational Data to Confirm Safety and Anticipate Threats
Sep 11, 2026Riccardo Donà, Espedito Rusciano, Germana Trentadue +2Autonomous Driving Data Collection
Seeing above the waves: A modular sensing framework for data acquisition at sea
Aug 11, 2026Jonathan E. Schmidt, Julius Wirbel, P. Nicholas Hansen +4Vessels Light Detection And Ranging
Data collection from highways: a geometric, class-agnostic approach to embedded vehicle counting
Aug 7, 2026Lucas Gouveia Omena Lopes, William W. M. Lira, Alexandre M. Lima +1Roadside Counting
ABC: Numerical Data Collection under Local Differential Privacy without Prior Knowledge
Aug 6, 2026Incheol Baek, Hyungbin Kim, Yon Dohn ChungDifferential Privacy Data Collection
Held-out evidence resolves follow-up measurement decisions in biological screens
Jul 30, 2026Jia Bi, Samuel Pinilla, Chenyang ZhuData Collection Evaluation Protocols
Scale Up Strategically: Learning Compositional Generalization via Bias-Aware Evaluation and Data Collection for Robotic Manipulation
Jul 23, 2026Yu Qi, Zhang Ye, Xinyi Xu +6Reinforcement-Learning Policies Robotic Manipulation
Data and Learning Where it Matters for Contact-Rich Manipulation
Jul 17, 2026Oliver Hausdörfer, Linus Schwarz, Gabor Marko +7Data Collection Contact-Rich Manipulation
Zero2Skill: Bootstrapping Robot Skills through Autonomous Data Collection, Training, and Deployment
Jul 15, 2026Boyuan Wang, Zhenyuan Zhang, Zhiqin Yang +16Real-Robot Experiments Human-In-The-Loop
How much Data do We Need? Sequential Data Collection for Stochastic Programming
Jul 11, 2026Xin Li, Juergen Branke, Xuan Vinh DoanOptimal Stopping Stochastic Optimization
Is Randomness Necessary for Adaptive Data Analysis?
Jul 8, 2026Edith Cohen, Haim Kaplan, Yishay Mansour +2Adaptive Adversary Data Collection
EVA-Client: A Unified Data Collection, Inference, and Deployment Framework for Embodied Policies on Real Robots
Jul 2, 2026Heqing Yang, Yang Yi, Liyao Wang +8Real-Robot Experiments Robots
Creating Impactful Autonomous Driving Datasets: A Strategic Guide from Research Gap to Benchmark
Jul 1, 2026Richard Schwarzkopf, Jonas Merkert, Frank Bieder +22Naturalistic Driving Data Data Collection
Making Failure Safe: A Constrained, Verifiable Agent Framework for Open-Web Data Collection
Jun 25, 2026Bo ChenAgentic Crawlers Data Collection
Efficient Adaptive Data Acquisition via Pretrained Belief Representations
Jun 23, 2026Daolang Huang, Zhuoyue Huang, Conor Hassan +3Data Collection Belief-Space Planning
TSD: A Physics-Inspired Trajectory Saliency Detector for Efficient Imitation Learning
Jun 22, 2026Yiming Zhao, Gongrui Ma, Qingkai Li +1Imitation Learning Robot Trajectories
From Speech to Text Corpora: Evaluating ASR-Based Data Acquisition for Low-Resource Fongbe and Hausa
Jun 20, 2026Mahounan Pericles Adjovi, Victor Olufemi, Roald Eiselen +1Low-Resource Languages Automatic Speech Recognition
Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey
Jun 9, 2026Vanessa Schmidt, Huy Hoang Nguyen, Cédric Jung +2Efficient Data Selection Large Language Model Training
An Adaptive Data cleaning Framework for Noisy Label Detection
Jun 5, 2026Chen-Hsuan Fang, Wei-Hsinag Chen, Pin-Hsuan Yu +2Noisy Labels Unsupervised Detectors
Hybrid Imbalanced Regression Through Unified Data-Level and Algorithm-Level Balancing
May 31, 2026Shermin Shahbazi, Hossein Mohammadi, Mohsen AfsharchiExtreme Class Imbalance Regression
Data Collection for Training Quality-Control AI in Carpet Manufacturing
May 31, 2026Akbar ErkinovInspection Defect
Optimal Data Acquisition for Reinforcement Learning: A Large Deviations Perspective
May 27, 2026Mingjie Hu, Jian-Qiang Hu, Enlu ZhouData Collection Lagrangian Relaxation
VR-DAgger: Immersive VR for Dexterous Data Collection and Uncertainty-Guided On-Policy Correction
May 26, 2026René Zurbrügg, Tifanny Portela, Arjun Bhardwaj +3Teleoperation Data Collection
EgoKit: Towards Unified Low-Cost Egocentric Data Collection with Heterogeneous Devices
May 16, 2026Liuchuan Yu, Erdem Murat, Beichen Wang +10Egocentric Dataset Egocentric Video
ROAD: Adaptive Data Mixing for Offline-to-Online Reinforcement Learning via Bi-Level Optimization
May 14, 2026Letian Yang, Xu Liu, Yiqiang Lu +3Offline Safe Reinforcement Learning Q-Learning
Post-ADC Inference: Valid Inference After Active Data Collection
May 12, 2026Shuichi Nishino, Tomohiro Shiraishi, Teruyuki Katsuoka +1Data Collection Post-Hoc
Adaptive Data Harvesting for Efficient Neural Network Learning with Universal Constraints
May 10, 2026Siteng Kang, Xinhua ZhangConventional Physics-Informed Neural Networks Adaptive Learning
Automated In-the-Wild Data Collection for Continual AI Generated Image Detection
May 4, 2026Thanasis Pantsios, Dimitrios Karageorgiou, Christos Koutlis +3Ai-Generated Image Detection Parameter-Efficient Adaptation
BaRA: Budget-constrained and Reliable Web Data Collection Agent
May 2, 2026Soojeong Lee, Joseph Lee, Yongseong Cho +3Web Agents Data Collection
An Object-Centered Data Acquisition Method for 3D Gaussian Splatting using Mobile Phones
Apr 21, 2026Yuezhe Zhang, Luqian Bai, Mengting Yu +33D Gaussian Splatting 3D Gaussian
Leveraging VR Robot Games to Facilitate Data Collection for Embodied Intelligence Tasks
Apr 18, 2026Yihan Zhang, Ziyun Huang, Linqi YeRobotic Data Acquisition Real-World Mobile Manipulation Tasks
DEX-Mouse: A Low-cost Portable and Universal Interface with Force Feedback for Data Collection of Dexterous Robotic Hands
Apr 16, 2026Joonho Koh, Haechan Jung, Nayoung Kim +2Robotic Hands Dexterous Manipulation
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms
Apr 4, 2024Miao Lu, Han Zhong, Tong Zhang +1Distributional Reinforcement Learning Markov Decision Processes

Sep 11, 2026 · cs.ROJ/K move · Enter open · S save

Using Automated Vehicles Operational Data to Confirm Safety and Anticipate Threats

Riccardo Donà, Espedito Rusciano, Germana Trentadue, Anastasios Tsakalidis+1

European Union (EU) policymakers adopted revolutionary data collection provisions for Automated Driving Systems (ADS) in the recently approved regulation that allows driverless vehicles to be operated on public roads. The framework is inspired by best practices developed at the United Nations Economic Commission for Europe(UNECE) level: the In-Service Monitoring and Reporting (ISMR); and by similar operational data collection regulatory approaches in nuclear energy production and transportation fields. The collection of real-world data will enable the competent safety authorities to gather the information needed to confirm the homologation safety target. Safety-relevant driving scenarios discovered during the real-world operation of a given ADS can also be stored in a scenario catalogue to investigate how other ADS types might have addressed such a traffic conflict. Moreover, lessons learnt deriving from the data collected can be shared among original equipment manufacturers (OEMs) and safety authorities. Ultimately, the ISMR is recognised as a necessary tool to properly tackle the challenges associated with ADS safety assessment given the number of unknowns that might remain undisclosed by leveraging the traditional homologation validation scheme only.

Autonomous Driving Data Collection AI Safety Alignment

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