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

649 papers, page 7 of 13

301. ICML 2023Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation
302. ICML 2023Reward-Mixing MDPs with Few Latent Contexts are Learnable
303. ICML 2023Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch
304. ICML 2023Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation
305. ICML 2023Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes
306. ICML 2023Sampling-Based Accuracy Testing of Posterior Estimators for General Inference
307. ICML 2023Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation
308. ICML 2023Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains
309. ICML 2023SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance
310. ICML 2023Shape-Guided Dual-Memory Learning for 3D Anomaly Detection
311. ICML 2023Sharper Bounds for $\ell_p$ Sensitivity Sampling
312. ICML 2023SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
313. ICML 2023SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series
314. ICML 2023Stable and Consistent Prediction of 3D Characteristic Orientation via Invariant Residual Learning
315. ICML 2023State and parameter learning with PARIS particle Gibbs
316. ICML 2023STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition
317. ICML 2023Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems
318. ICML 2023The Edge of Orthogonality: A Simple View of What Makes BYOL Tick
319. ICML 2023Theory on Forgetting and Generalization of Continual Learning
320. ICML 2023Toward Large Kernel Models
321. ICML 2023Towards Understanding Generalization of Macro-AUC in Multi-label Learning
322. ICML 2023Transformers as Algorithms: Generalization and Stability in In-context Learning
323. ICML 2023UMD: Unsupervised Model Detection for X2X Backdoor Attacks
324. ICML 2023Underspecification Presents Challenges for Credibility in Modern Machine Learning
325. ICML 2023Understanding and Generalizing Contrastive Learning from the Inverse Optimal Transport Perspective
326. ICML 2023Unearthing InSights into Mars: Unsupervised Source Separation with Limited Data
327. ICML 2023Unlocking Slot Attention by Changing Optimal Transport Costs
328. ICML 2023Unsupervised Out-of-Distribution Detection with Diffusion Inpainting
329. ICML 2023Unsupervised Skill Discovery for Learning Shared Structures across Changing Environments
330. ICML 2023Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills
331. ICML 2023Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression
332. NeurIPS 2023(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
333. NeurIPS 2023$H$-Consistency Bounds: Characterization and Extensions
334. NeurIPS 2023$L_2$-Uniform Stability of Randomized Learning Algorithms: Sharper Generalization Bounds and Confidence Boosting
335. NeurIPS 2023$p$-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison
336. NeurIPS 2023$SE(3)$ Equivariant Convolution and Transformer in Ray Space
337. NeurIPS 2023A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings
338. NeurIPS 2023A Competitive Algorithm for Agnostic Active Learning
339. NeurIPS 2023A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games
340. NeurIPS 2023A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions
341. NeurIPS 2023A General Framework for Equivariant Neural Networks on Reductive Lie Groups
342. NeurIPS 2023A General Framework for Robust G-Invariance in G-Equivariant Networks
343. NeurIPS 2023A General Theory of Correct, Incorrect, and Extrinsic Equivariance
344. NeurIPS 2023A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
345. NeurIPS 2023A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories
346. NeurIPS 2023A Theory of Transfer-Based Black-Box Attacks: Explanation and Implications
347. NeurIPS 2023A Theory of Unsupervised Translation Motivated by Understanding Animal Communication
348. NeurIPS 2023A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning
349. NeurIPS 2023A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process
350. NeurIPS 2023A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm

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.