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

833 papers, page 10 of 17

451. NeurIPS 2024Latent Intrinsics Emerge from Training to Relight
452. NeurIPS 2024Learning Commonality, Divergence and Variety for Unsupervised Visible-Infrared Person Re-identification
453. NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
454. NeurIPS 2024Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
455. NeurIPS 2024Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees
456. NeurIPS 2024Learning Segmentation from Point Trajectories
457. NeurIPS 2024Learning to Embed Distributions via Maximum Kernel Entropy
458. NeurIPS 2024Learning Versatile Skills with Curriculum Masking
459. NeurIPS 2024Leveraging Separated World Model for Exploration in Visually Distracted Environments
460. NeurIPS 2024Linear Causal Bandits: Unknown Graph and Soft Interventions
461. NeurIPS 2024Logical characterizations of recurrent graph neural networks with reals and floats
462. NeurIPS 2024MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
463. NeurIPS 2024MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts
464. NeurIPS 2024Markov Equivalence and Consistency in Differentiable Structure Learning
465. NeurIPS 2024Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration
466. NeurIPS 2024Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms
467. NeurIPS 2024NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
468. NeurIPS 2024No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation
469. NeurIPS 2024Nonlinear dynamics of localization in neural receptive fields
470. NeurIPS 2024On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
471. NeurIPS 2024On the Expressive Power of Tree-Structured Probabilistic Circuits
472. NeurIPS 2024On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
473. NeurIPS 2024Online Budgeted Matching with General Bids
474. NeurIPS 2024Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
475. NeurIPS 2024Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL
476. NeurIPS 2024PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning
477. NeurIPS 2024Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers
478. NeurIPS 2024Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis
479. NeurIPS 2024Plant-and-Steal: Truthful Fair Allocations via Predictions
480. NeurIPS 2024Probabilistic size-and-shape functional mixed models
481. NeurIPS 2024Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation
482. NeurIPS 2024Real-Time Selection Under General Constraints via Predictive Inference
483. NeurIPS 2024Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
484. NeurIPS 2024REBORN: Reinforcement-Learned Boundary Segmentation with Iterative Training for Unsupervised ASR
485. NeurIPS 2024Reconstruct and Match: Out-of-Distribution Robustness via Topological Homogeneity
486. NeurIPS 2024Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery
487. NeurIPS 2024Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation
488. NeurIPS 2024RMLR: Extending Multinomial Logistic Regression into General Geometries
489. NeurIPS 2024Robust group and simultaneous inferences for high-dimensional single index model
490. NeurIPS 2024Robust Reinforcement Learning with General Utility
491. NeurIPS 2024Safe and Efficient: A Primal-Dual Method for Offline Convex CMDPs under Partial Data Coverage
492. NeurIPS 2024Sample-Efficient Constrained Reinforcement Learning with General Parameterization
493. NeurIPS 2024Semantic Feature Learning for Universal Unsupervised Cross-Domain Retrieval
494. NeurIPS 2024Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics
495. NeurIPS 2024Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood
496. NeurIPS 2024Simplified and Generalized Masked Diffusion for Discrete Data
497. NeurIPS 2024SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions
498. NeurIPS 2024Small coresets via negative dependence: DPPs, linear statistics, and concentration
499. NeurIPS 2024Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
500. NeurIPS 2024Symmetries in Overparametrized Neural Networks: A Mean Field View

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.