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

2,682 papers, page 14 of 54

651. NeurIPS 2026Evaluating Test-Time Scaling of General LLM Agents
652. NeurIPS 2026Fast Approximate $\ell_p$ Chamfer Distance via Lopsided Embeddings and Structured JL
653. NeurIPS 2026Finding Koopman Invariant Subspaces via Personalized PageRank
654. NeurIPS 2026Fisher information and the geometry of memorization in neural networks
655. NeurIPS 2026Fixed-Size Active Statistical Inference
656. NeurIPS 2026FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting
657. NeurIPS 2026Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models
658. NeurIPS 2026FOGO: Forgetting-aware Orthogonalization Optimizer
659. NeurIPS 2026Free Decompression with Algebraic Spectral Curves
660. NeurIPS 2026From Contexts to Conditionals: Statistical Self-Consistency of Persona Prompting
661. NeurIPS 2026FuncFormer: Circuit Representation Learning via the Flow of Functional Propagation
662. NeurIPS 2026General Agent Evaluation
663. NeurIPS 2026Generalizing the Geometry of Model Merging Through Fréchet Averages
664. NeurIPS 2026Geometry Matters in Packed 3D Attention
665. NeurIPS 2026GISA: A Benchmark for General Information-Seeking Assistant
666. NeurIPS 2026Global Convergence of Four-Layer Matrix Factorization under Random Initialization
667. NeurIPS 2026GPA: General Principled Framework for Linearizing Softmax Attention via KV Cache Approximation
668. NeurIPS 2026Grounded or Fabricated? Unsupervised Detection of LLM Hallucinations via Contextualized Influence on Response Embeddings
669. NeurIPS 2026Hallucination-Guided Unlearning: Using Hallucination Traces to Reveal Overfitted Memories
670. NeurIPS 2026HARC: Coupling Harmfulness and Refusal Capabilities for Robust Safety Alignment
671. NeurIPS 2026HoloGene: Learning to Lift Sliced Spatial Transcriptomics to Holistic 3D Gene Fields
672. NeurIPS 2026How Can SignSGD Outperform SGD? A Functional Scaling Law Perspective
673. NeurIPS 2026How Do Language Models Compose Functions?
674. NeurIPS 2026Hyperagents
675. NeurIPS 2026Hypergraph Representation Learning with Hyperlink Random Effects
676. NeurIPS 2026HyperTree: Scalable Unsupervised Hierarchy Discovery in Hyperbolic Space
677. NeurIPS 2026Improving General Role-Playing Agents via Psychology-Grounded Reasoning and Role-Aware Policy Optimization
678. NeurIPS 2026Indications of Belief-Guided Agency and Meta-Cognitive Monitoring in Large Language Models
679. NeurIPS 2026Inference and Uncertainty Quantification for Streaming $r$-PCA
680. NeurIPS 2026Integrating Local and Global Entropy for Uncertainty Quantification in LLMs
681. NeurIPS 2026Internal Evaluation of Unsupervised Anomaly Detection Algorithms with Explanation
682. NeurIPS 2026Intrinsic Information Theoretic Analysis of ReLU Nets
683. NeurIPS 2026Invariant Features in Language Models: Geometric Characterization and Model Attribution
684. NeurIPS 2026Inverse Linear Bandits via Linear Programs
685. NeurIPS 2026Learn from your own latents and not from tokens: A sample-complexity theory
686. NeurIPS 2026Learning a Maximum Entropy Model for Visual Textures using Diffusion
687. NeurIPS 2026Learning Augmented Exact Exponential Algorithms
688. NeurIPS 2026Learning Causal Orderings for In-Context Tabular Prediction
689. NeurIPS 2026Learning Informative Invariant Representations via Hierarchical Latent Decomposition
690. NeurIPS 2026Learning Menu-Based Mechanisms for Truthful Budget-Feasible Procurement
691. NeurIPS 2026Learning Modular Addition with Auxiliary Modulus
692. NeurIPS 2026Learning Optimal Transport Plans Via Autoregressive Token Regression
693. NeurIPS 2026Learning Orthonormal Bases for Function Spaces
694. NeurIPS 2026Learning to Bid in Repeated Second-Price Auctions with Dynamic Values and Aggregated Feedback
695. NeurIPS 2026Learning to Persuade a Biased Receiver
696. NeurIPS 2026Learning to play with spikes. Characterizing, predicting, and engineering unsupervised plasticity rules for spiking reservoir computing
697. NeurIPS 2026LIBERO-PeRM: Benchmarking Personalized Robotic Manipulation
698. NeurIPS 2026Local Sparsity Enables Unsupervised LLM Safety Detection
699. NeurIPS 2026LookWhen? Fast Video Recognition by Learning When, Where, and What to Compute
700. NeurIPS 2026Manifold Random Features

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.