Data Cleaning papers, 2023–2026

Key findings

• Data Cleaning fell from 21 papers in 2023 to 10 in 2026, so interest is cooling.
• ICML publishes the most Data Cleaning work: 17 papers from 2023 to 2026, 35% of the four-venue total.
• Among the 5 topics under Data-Centric AI, it ranks #5 by 2026 paper count; the fastest grower in the group, Synthetic Data Generation, is up 1.3x versus 0.5x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026GradTrack: Detecting Noisy Labels via Temporal Trajectories of Class-wise Gradient Misalignment
• ICML 2026Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels
• ICLR 2026Enhancing Learning with Noisy Labels via Rockafellian Relaxation
• CVPR 2026Cleaning the Pool Progressive Filtering of Unlabeled Pools in Deep
• NeurIPS 2025Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples
• ICML 2025Free Process Rewards without Process Labels
• ICLR 2025Learning to Generate Diverse Pedestrian Movements from Web Videos with Noisy Labels
• CVPR 2025Directional Label Diffusion Model for Learning from Noisy Labels
• ICML 2024Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical
• CVPR 2024Estimating Noisy Class Posterior with Part-level Labels for Noisy Label Learning
• NeurIPS 2023Label Correction of Crowdsourced Noisy Annotations with an Instance-Dependent Noise Transition Model
• ICML 2023Data Structures for Density Estimation
• ICLR 2023Learning to Segment from Noisy Annotations: A Spatial Correction Approach
• CVPR 2023Fine-Grained Classification With Noisy Labels
• NeurIPS 2026Memorization Is Folding: Topological Signatures of Noisy-Label Learning
• CVPR 2026Debiased Sample Selection for Learning with Noisy Labels
• NeurIPS 2025ELDET: Early-Learning Distillation with Noisy Labels for Object Detection
• ICML 2025Retraining with Predicted Hard Labels Provably Increases Model Accuracy
• ICML 2024Pi-DUAL: Using privileged information to distinguish clean from noisy labels
• CVPR 2024Learning with Structural Labels for Learning with Noisy Labels

All Data Cleaning papers

9 papers, page 1 of 1

1. ICML 20232D-Shapley: A Framework for Fragmented Data Valuation
2. ICML 2023Data Structures for Density Estimation
3. ICML 2023Data-Derived Weak Universal Consistency
4. ICML 2023Generating Private Synthetic Data with Genetic Algorithms
5. ICML 2023Gradient-Free Structured Pruning with Unlabeled Data
6. ICML 2023Learning Functional Distributions with Private Labels
7. ICML 2023Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation
8. ICML 2023Mitigating Memorization of Noisy Labels by Clipping the Model Prediction
9. ICML 2023Unearthing InSights into Mars: Unsupervised Source Separation with Limited Data

FAQ

How many Data Cleaning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

48 in total: 21 in 2023, 11 in 2024, 6 in 2025, 10 in 2026.

How many Data Cleaning papers are at NeurIPS 2026?

NeurIPS 2026 has 6 Data Cleaning papers, versus 2 the year before.

How many Data Cleaning papers are at ICLR 2026?

ICLR 2026 has 1 Data Cleaning papers, versus 1 the year before.

How many Data Cleaning papers are at ICML 2026?

ICML 2026 has 1 Data Cleaning papers, versus 2 the year before.

How many Data Cleaning papers are at CVPR 2026?

CVPR 2026 has 2 Data Cleaning papers, versus 1 the year before.

Which conference publishes the most Data Cleaning papers?

ICML, with 17 papers from 2023 to 2026.