Active Learning papers, 2023–2026

Key findings

• Active Learning fell from 58 papers in 2023 to 41 in 2026, so interest is cooling.
• NeurIPS publishes the most Active Learning work: 67 papers from 2023 to 2026, 41% of the four-venue total.
• The fastest-growing overlap is with 3D Vision: papers tagged with both rose from 0 in 2023 to 6 in 2026.
• Among the 5 topics under Data-Centric AI, it ranks #3 by 2026 paper count; the fastest grower in the group, Synthetic Data Generation, is up 1.3x versus 0.7x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Active Corpus Selection for Training Subgraph Retrievers Using OOD Queries
• ICML 2026Active Regression for Single-Index Models with Unknown Link Functions
• ICLR 2026ActiveCQ: Active Estimation of Causal Quantities
• CVPR 2026Active Inference for Micro-Gesture Recognition EFE-Guided Temporal Sampling and Adaptive
• NeurIPS 2025Active Measurement: Efficient Estimation at Scale
• ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
• ICLR 2025Dual Process Learning: Controlling Use of In-Context vs. In-Weights Strategies with Weight Forgetting
• CVPR 2025Active Hyperspectral Imaging Using an Event Camera
• NeurIPS 2024On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
• ICML 2024Active Statistical Inference
• ICLR 2024Improved Active Learning via Dependent Leverage Score Sampling
• CVPR 2024NARUTO: Neural Active Reconstruction from Uncertain Target Observations
• NeurIPS 2023A Competitive Algorithm for Agnostic Active Learning
• ICML 2023A Two-Stage Active Learning Algorithm for k-Nearest Neighbors
• ICLR 2023A Simple Yet Powerful Deep Active Learning With Snapshots Ensembles
• CVPR 2023Re-Thinking Federated Active Learning Based on Inter-Class Diversity
• NeurIPS 2026Active Learning as Nullspace Regulation: A Spectral Representation Perspective
• ICML 2026Active Timepoint Selection for Learning Measure-Valued Trajectories
• ICLR 2026TESSAR: Geometry-Aware Active Regression via Dynamic Voronoi Tessellation
• CVPR 2026EventHub Data Factory for Generalizable Event-Based Stereo Networks without Active

All Active Learning papers

58 papers, page 1 of 2

1. CVPR 2023A Light Weight Model for Active Speaker Detection
2. CVPR 2023Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning Paradigm
3. CVPR 2023AShapeFormer: Semantics-Guided Object-Level Active Shape Encoding for 3D Object Detection via Transformers
4. CVPR 2023Bi3D: Bi-Domain Active Learning for Cross-Domain 3D Object Detection
5. CVPR 2023Box-Level Active Detection
6. CVPR 2023Re-Thinking Federated Active Learning Based on Inter-Class Diversity
7. ICLR 2023A Simple Yet Powerful Deep Active Learning With Snapshots Ensembles
8. ICLR 2023Active Image Indexing
9. ICLR 2023Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle
10. ICLR 2023BALTO: fast tensor program optimization with diversity-based active learning
11. ICLR 2023Leveraging Importance Weights in Subset Selection
12. ICLR 2023MCAL: Minimum Cost Human-Machine Active Labeling
13. ICLR 2023Robust Active Distillation
14. ICLR 2023Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing
15. ICLR 2023Scalable Subset Sampling with Neural Conditional Poisson Networks
16. ICLR 2023Selective Annotation Makes Language Models Better Few-Shot Learners
17. ICML 2023A Two-Stage Active Learning Algorithm for k-Nearest Neighbors
18. ICML 2023Active Learning based Structural Inference
19. ICML 2023Active Policy Improvement from Multiple Black-box Oracles
20. ICML 2023Anchor Sampling for Federated Learning with Partial Client Participation
21. ICML 2023Gibbsian Polar Slice Sampling
22. ICML 2023LSDS++ : Dual Sampling for Accelerated k-means++
23. ICML 2023Margin-based sampling in high dimensions: When being active is less efficient than staying passive
24. ICML 2023NNSplitter: An Active Defense Solution for DNN Model via Automated Weight Obfuscation
25. ICML 2023On Sampling with Approximate Transport Maps
26. ICML 2023SAAL: Sharpness-Aware Active Learning
27. ICML 2023Streaming Active Learning with Deep Neural Networks
28. ICML 2023Towards Controlled Data Augmentations for Active Learning
29. ICML 2023Training-Free Neural Active Learning with Initialization-Robustness Guarantees
30. NeurIPS 2023A Competitive Algorithm for Agnostic Active Learning
31. NeurIPS 2023Active Bipartite Ranking
32. NeurIPS 2023Active Learning-Based Species Range Estimation
33. NeurIPS 2023Active Negative Loss Functions for Learning with Noisy Labels
34. NeurIPS 2023Active Vision Reinforcement Learning under Limited Visual Observability
35. NeurIPS 2023Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice
36. NeurIPS 2023Adaptive Selective Sampling for Online Prediction with Experts
37. NeurIPS 2023Agnostic Multi-Group Active Learning
38. NeurIPS 2023Algorithm Selection for Deep Active Learning with Imbalanced Datasets
39. NeurIPS 2023Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets
40. NeurIPS 2023Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders
41. NeurIPS 2023Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions
42. NeurIPS 2023Cross-modal Active Complementary Learning with Self-refining Correspondence
43. NeurIPS 2023DELTA: Diverse Client Sampling for Fasting Federated Learning
44. NeurIPS 2023Epidemic Learning: Boosting Decentralized Learning with Randomized Communication
45. NeurIPS 2023FIRAL: An Active Learning Algorithm for Multinomial Logistic Regression
46. NeurIPS 2023How Re-sampling Helps for Long-Tail Learning?
47. NeurIPS 2023How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget
48. NeurIPS 2023Improving Language Plasticity via Pretraining with Active Forgetting
49. NeurIPS 2023Likelihood Ratio Confidence Sets for Sequential Decision Making
50. NeurIPS 2023Model-Free Active Exploration in Reinforcement Learning

FAQ

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

165 in total: 58 in 2023, 35 in 2024, 31 in 2025, 41 in 2026.

How many Active Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 16 Active Learning papers, versus 9 the year before.

How many Active Learning papers are at ICLR 2026?

ICLR 2026 has 6 Active Learning papers, versus 7 the year before.

How many Active Learning papers are at ICML 2026?

ICML 2026 has 8 Active Learning papers, versus 7 the year before.

How many Active Learning papers are at CVPR 2026?

CVPR 2026 has 11 Active Learning papers, versus 8 the year before.

Which conference publishes the most Active Learning papers?

NeurIPS, with 67 papers from 2023 to 2026.