General ML · unsupervised and semisupervised learning papers, 2023–2026

Key findings

• General ML · unsupervised and semisupervised learning went from 649 papers in 2023 to 799 in 2026, roughly 1.2x in three years.
• ICML publishes the most General ML · unsupervised and semisupervised learning work: 859 papers from 2023 to 2026, 32% of the four-venue total.
• The fastest-growing overlap is with Deep learning · self supervised learning: papers tagged with both rose from 23 in 2023 to 86 in 2026.
• Among the 6 topics under General Machine Learning, it ranks #1 by 2026 paper count; the fastest grower in the group, General ML · evaluation, is up 4.3x versus 1.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A general kernel framework for non-CND distance measures using $|\mathcal{D}|$-dimensional sparse landmark embeddings
• ICML 2026$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
• ICLR 2026A Generalized Geometric Theoretical Framework of Centroid Discriminant Analysis for Linear Classification of Multi-dimensional Data
• CVPR 2026COG Confidence-aware Optimal Geometric Correspondence for Unsupervised Single-reference Novel Object
• NeurIPS 2025$O(\sqrt{T})$ Static Regret and Instance Dependent Constraint Violation for Constrained Online Convex Optimization
• ICML 2025A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
• ICLR 2025A General Framework for Producing Interpretable Semantic Text Embeddings
• CVPR 2025A General Adaptive Dual-level Weighting Mechanism for Remote Sensing Pansharpening
• NeurIPS 2024GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages
• ICML 2024CKGConv: General Graph Convolution with Continuous Kernels
• ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
• CVPR 2024Dual Prototype Attention for Unsupervised Video Object Segmentation
• NeurIPS 2023$H$-Consistency Bounds: Characterization and Extensions
• ICML 2023A Mathematical Model for Curriculum Learning for Parities
• ICLR 2023A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
• CVPR 2023A General Regret Bound of Preconditioned Gradient Method for DNN Training
• NeurIPS 2026Attention-based PCA
• ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
• ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
• CVPR 2026CROWn A Unified Framework for Anti-Aliased Downsampling and Phase-Calibrated Fusion

All General ML · unsupervised and semisupervised learning papers

553 papers, page 11 of 12

501. NeurIPS 2024MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts
502. NeurIPS 2024Markov Equivalence and Consistency in Differentiable Structure Learning
503. NeurIPS 2024Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration
504. NeurIPS 2024Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms
505. NeurIPS 2024NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
506. NeurIPS 2024No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation
507. NeurIPS 2024Nonlinear dynamics of localization in neural receptive fields
508. NeurIPS 2024On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
509. NeurIPS 2024On the Expressive Power of Tree-Structured Probabilistic Circuits
510. NeurIPS 2024On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
511. NeurIPS 2024Online Budgeted Matching with General Bids
512. NeurIPS 2024Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
513. NeurIPS 2024Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL
514. NeurIPS 2024PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning
515. NeurIPS 2024Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers
516. NeurIPS 2024Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis
517. NeurIPS 2024Plant-and-Steal: Truthful Fair Allocations via Predictions
518. NeurIPS 2024Probabilistic size-and-shape functional mixed models
519. NeurIPS 2024Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation
520. NeurIPS 2024Real-Time Selection Under General Constraints via Predictive Inference
521. NeurIPS 2024Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
522. NeurIPS 2024REBORN: Reinforcement-Learned Boundary Segmentation with Iterative Training for Unsupervised ASR
523. NeurIPS 2024Reconstruct and Match: Out-of-Distribution Robustness via Topological Homogeneity
524. NeurIPS 2024Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery
525. NeurIPS 2024Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation
526. NeurIPS 2024RMLR: Extending Multinomial Logistic Regression into General Geometries
527. NeurIPS 2024Robust group and simultaneous inferences for high-dimensional single index model
528. NeurIPS 2024Robust Reinforcement Learning with General Utility
529. NeurIPS 2024Safe and Efficient: A Primal-Dual Method for Offline Convex CMDPs under Partial Data Coverage
530. NeurIPS 2024Sample-Efficient Constrained Reinforcement Learning with General Parameterization
531. NeurIPS 2024Semantic Feature Learning for Universal Unsupervised Cross-Domain Retrieval
532. NeurIPS 2024Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics
533. NeurIPS 2024Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood
534. NeurIPS 2024Simplified and Generalized Masked Diffusion for Discrete Data
535. NeurIPS 2024SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions
536. NeurIPS 2024Small coresets via negative dependence: DPPs, linear statistics, and concentration
537. NeurIPS 2024Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
538. NeurIPS 2024Symmetries in Overparametrized Neural Networks: A Mean Field View
539. NeurIPS 2024The Mamba in the Llama: Distilling and Accelerating Hybrid Models
540. NeurIPS 2024The Star Geometry of Critic-Based Regularizer Learning
541. NeurIPS 2024Time-Reversal Provides Unsupervised Feedback to LLMs
542. NeurIPS 2024Toward Real Ultra Image Segmentation: Leveraging Surrounding Context to Cultivate General Segmentation Model
543. NeurIPS 2024Towards General Loop Invariant Generation: A Benchmark of Programs with Memory Manipulation
544. NeurIPS 2024Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and A Certified Baseline
545. NeurIPS 2024Towards Unsupervised Model Selection for Domain Adaptive Object Detection
546. NeurIPS 2024Transformers Represent Belief State Geometry in their Residual Stream
547. NeurIPS 2024UNION: Unsupervised 3D Object Detection using Object Appearance-based Pseudo-Classes
548. NeurIPS 2024Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need?
549. NeurIPS 2024Unsupervised Anomaly Detection in The Presence of Missing Values
550. NeurIPS 2024Unsupervised Discovery of Formulas for Mathematical Constants

FAQ

How many General ML · unsupervised and semisupervised learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,683 in total: 649 in 2023, 553 in 2024, 682 in 2025, 799 in 2026.

How many General ML · unsupervised and semisupervised learning papers are at NeurIPS 2026?

NeurIPS 2026 has 194 General ML · unsupervised and semisupervised learning papers, versus 203 the year before.

How many General ML · unsupervised and semisupervised learning papers are at ICLR 2026?

ICLR 2026 has 187 General ML · unsupervised and semisupervised learning papers, versus 174 the year before.

How many General ML · unsupervised and semisupervised learning papers are at ICML 2026?

ICML 2026 has 348 General ML · unsupervised and semisupervised learning papers, versus 239 the year before.

How many General ML · unsupervised and semisupervised learning papers are at CVPR 2026?

CVPR 2026 has 70 General ML · unsupervised and semisupervised learning papers, versus 66 the year before.

Which conference publishes the most General ML · unsupervised and semisupervised learning papers?

ICML, with 859 papers from 2023 to 2026.