mlsanityData to 7 Oct 2026

Data-centric AI: Perspectives and Challenges

arXiv 2301.04819 ↗First posted 12 Jan 2023cs.AI cs.LGcited by 43

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Abstract (arXiv)

The role of data in building AI systems has recently been significantly magnified by the emerging concept of data-centric AI (DCAI), which advocates a fundamental shift from model advancements to ensuring data quality and reliability. Although our community has continuously invested efforts into enhancing data in different aspects, they are often isolated initiatives on specific tasks. To facilitate the collective initiative in our community and push forward DCAI, we draw a big picture and bring together three general missions: training data development, inference data development, and data maintenance. We provide a top-level discussion on representative DCAI tasks and share perspectives. Finally, we list open challenges. More resources are summarized at https://github.com/daochenzha/data-centric-AI

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). Builds on 25 of its 55 references that are in the map. First posted on arXiv 12 Jan 2023.

Builds on

25 of 55 references.

References · 25

  1. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
  2. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,911
  3. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,255
  4. 2019Modeling Tabular data using Conditional GANcited by 695
  5. 2020A Survey of Deep Active Learningcited by 547
  6. 2021A Survey of Data Augmentation Approaches for NLPcited by 408
  7. 2020Algorithmic Recourse: from Counterfactual Explanations to Interventionscited by 250
  8. 2016Data Programming: Creating Large Training Sets, Quicklycited by 246
  9. 2020Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learningcited by 174
  10. 2022DataPerf: Benchmarks for Data-Centric AI Developmentcited by 89
  11. 2018Automated Data Slicing for Model Validation:A Big data - AI Integration Approachcited by 70
  12. 2021Self-Training with Weak Supervisioncited by 49
13 more
  1. 2020TODS: An Automated Time Series Outlier Detection Systemcited by 41
  2. 2020Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learningcited by 34
  3. 2020Dataset Discovery in Data Lakescited by 31
  4. 2022Data-Centric Artificial Intelligencecited by 31
  5. 2022The Principles of Data-Centric AI (DCAI)cited by 26
  6. 2021What can Data-Centric AI Learn from Data and ML Engineering?cited by 24
  7. 2019DeepLine: AutoML Tool for Pipelines Generation using Deep Reinforcement Learning and Hierarchical Actions Filteringcited by 21
  8. 2019Learning Credible Deep Neural Networks with Rationale Regularizationcited by 18
  9. 2021DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samplescited by 18
  10. 2017Multi-label Dataless Text Classification with Topic Modelingcited by 14
  11. 2022Towards Similarity-Aware Time-Series Classificationcited by 13
  12. 2022Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learningcited by 9
  13. 2021AutoVideo: An Automated Video Action Recognition Systemcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 18; 2024: 13; 2025: 6; 2026: 6.

43 papers.

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  1. 2023Data-centric Artificial Intelligence: A Surveycited by 202
  2. 2023FinGPT: Democratizing Internet-scale Data for Financial Large Language Modelscited by 65
  3. 2024A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensationcited by 57
  4. 2023Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learningcited by 41
  5. 2023FuseCap: Leveraging Large Language Models for Enriched Fused Image Captionscited by 33
  6. 2023OpenGSL: A Comprehensive Benchmark for Graph Structure Learningcited by 30
  7. 2023ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphscited by 27
  8. 2026MinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scalecited by 26
  9. 2024Generative Dataset Distillation: Balancing Global Structure and Local Detailscited by 18
  10. 2024Purify Unlearnable Examples via Rate-Constrained Variational Autoencoderscited by 18
  11. 2024From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Datacited by 18
  12. 2023Dynamic Datasets and Market Environments for Financial Reinforcement Learningcited by 15
31 more
  1. 2023Towards Data-centric Graph Machine Learning: Review and Outlookcited by 15
  2. 2023ActiveGLAE: A Benchmark for Deep Active Learning with Transformerscited by 14
  3. 2023Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networkscited by 14
  4. 2023Learning Physics-Informed Noise Models from Dark Frames for Low-Light Raw Image Denoisingcited by 10
  5. 2024Computer Vision for Primate Behavior Analysis in the Wildcited by 10
  6. 2023A Data-Centric Solution to NonHomogeneous Dehazing via Vision Transformercited by 9
  7. 2023VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Modelscited by 9
  8. 2023Context-aware Domain Adaptation for Time Series Anomaly Detectioncited by 8
  9. 2024XEdgeAI: A Human-centered Industrial Inspection Framework with Data-centric Explainable Edge AI Approachcited by 7
  10. 2024Investigating the Impact of Balancing, Filtering, and Complexity on Predictive Multiplicity: A Data-Centric Perspectivecited by 7
  11. 2024Promoting Fairness in Link Prediction with Graph Enhancementcited by 6
  12. 2025GraphPrompter: Multi-stage Adaptive Prompt Optimization for Graph In-Context Learningcited by 6
  13. 2023Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Modelscited by 5
  14. 2023Transition Role of Entangled Data in Quantum Machine Learningcited by 5
  15. 2024WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarkingcited by 5
  16. 2024Adaptive Data Quality Scoring Operations Framework using Drift-Aware Mechanism for Industrial Applicationscited by 4
  17. 2025Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challengecited by 4
  18. 2024Promoting the Responsible Development of Speech Datasets for Mental Health and Neurological Disorders Researchcited by 3
  19. 2024Survey and Taxonomy: The Role of Data-Centric AI in Transformer-Based Time Series Forecastingcited by 3
  20. 2025Generative Artificial Intelligence for Internet of Things Computing: A Systematic Surveycited by 3
  21. 2023DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Researchcited by 2
  22. 2023Towards Personalized Preprocessing Pipeline Searchcited by 1
  23. 2024Motif-driven Subgraph Structure Learning for Graph Classificationcited by 1
  24. 2025Data Quality Challenges in Retrieval-Augmented Generationcited by 1
  25. 2025Data-Centric AI for Tropical Agricultural Mapping: Challenges, Strategies and Scalable Solutionscited by 1
  26. 2026Data Distribution Matters: A Data-Centric Perspective on Context Compression for Large Language Modelcited by 1
  27. 2026Probabilistic Label Spreading: Efficient and Consistent Estimation of Soft Labels with Epistemic Uncertainty on Graphscited by 1
  28. 2025Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labelscited by 0
  29. 2026Stringalign: Moving beyond summary statistics with a transparent Unicode-aware tool for evaluating automatic transcription modelscited by 0
  30. 2026Vision: Data-Centric Anchoring for Robust and Interpretable Agentic AIcited by 0
  31. 2026Scalable, Transferable Meta-network for Data Selection Requires a Different Loss (and Why the Obvious Choice is Problematic)cited by 0