Theory · learning theory papers, 2023–2026
Theory area: learning_theory
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 1,350 papers are tagged with this topic.
Key findings
- Theory · learning theory went from 86 papers in 2023 to 482 in 2026, roughly 5.6x in three years.
- NeurIPS publishes the most Theory · learning theory work: 540 papers from 2023 to 2026, 40% of the four-venue total.
- The fastest-growing overlap is with Social aspects · accountability transparency and interpretability: papers tagged with both rose from 0 in 2023 to 33 in 2026.
- Among the 5 topics under Theory and Statistics, it ranks #2 by 2026 paper count; the fastest grower in the group, Theory · optimization, is up 4.7x versus 5.6x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 57 | 24 | 5 | 0 | 86 |
| 2024 | 265 | 106 | 21 | 1 | 393 |
| 2025 | 106 | 147 | 132 | 4 | 389 |
| 2026 | 112 | 200 | 170 | 0 | 482 |
Representative papers
Spread across years and venues so every edition shows up
- NeurIPS 2026A dynamical systems theory of reward-modulated learning in linear recurrent networks
- ICML 2026A Fine-Grained Understanding of Uniform Convergence for Halfspaces
- ICLR 2026A Law of Data Reconstruction for Random Features (And Beyond)
- NeurIPS 2025A Geometric Analysis of PCA
- ICML 2025A Generalization Theory for Zero-Shot Prediction
- ICLR 2025A Solvable Attention for Neural Scaling Laws
- CVPR 2025Dynamic Stereotype Theory Induced Micro-expression Recognition with Oriented Deformation
- NeurIPS 20244+3 Phases of Compute-Optimal Neural Scaling Laws
- ICML 2024A Statistical Theory of Regularization-Based Continual Learning
- ICLR 2024A Sublinear Adversarial Training Algorithm
- CVPR 2024Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory
- NeurIPS 2023$\varepsilon$-fractional core stability in Hedonic Games.
- ICML 2023Robust Collaborative Learning with Linear Gradient Overhead
- ICLR 2023Bispectral Neural Networks
- NeurIPS 2026A Mechanistic Investigation of Theory of Mind in a Large Language Model
- ICML 2026A Random Matrix Theory of Masked Self-Supervised Learning
- ICLR 2026A New Approach to Controlling Linear Dynamical Systems
- NeurIPS 2025Approximation theory for 1-Lipschitz ResNets
- ICML 2025A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
- ICLR 2025A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
All Theory · learning theory papers
482 papers, page 1 of 10
- ICLR 2026A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond
- ICLR 2026A Law of Data Reconstruction for Random Features (And Beyond)
- ICLR 2026A Near-Optimal Best-of-Both-Worlds Algorithm for Federated Bandits
- ICLR 2026A New Approach to Controlling Linear Dynamical Systems
- ICLR 2026A New Initialization to Control Gradients in Sinusoidal Neural Networks
- ICLR 2026A Recovery Guarantee for Sparse Neural Networks
- ICLR 2026A Representer Theorem for Hawkes Processes via Penalized Least Squares Minimization
- ICLR 2026A Sharp KL-Convergence Analysis for Diffusion Models under Minimal Assumptions
- ICLR 2026A Statistical Theory of Overfitting for Imbalanced Classification
- ICLR 2026A Theoretical Analysis of Mamba’s Training Dynamics: Filtering Relevant Features for Generalization in State Space Models
- ICLR 2026A Unifying View of Coverage in Linear Off-policy Evaluation
- ICLR 2026Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry
- ICLR 2026Action Chunking and Data Augmentation Yield Exponential Improvements in Behavior Cloning for Continuous Spaces
- ICLR 2026Active Learning for Decision Trees with Provable Guarantees
- ICLR 2026Adversarially Pretrained Transformers may be Universally Robust In-Context Learners
- ICLR 2026Almost Bayesian: Dynamics of SGD Through Singular Learning Theory
- ICLR 2026An efficient, provably optimal, practical algorithm for the 0-1 loss linear classification problem
- ICLR 2026An Improved Model-free Decision-estimation Coefficient with Applications in Adversarial MDPs
- ICLR 2026Automata Learning and Identification of the Support of Language Models
- ICLR 2026Bandit Learning in Matching Markets Robust to Adversarial Corruptions
- ICLR 2026Barriers for Learning in an Evolving World: Mathematical Understanding of Loss of Plasticity
- ICLR 2026Benefits and Limitations of Communication in Multi-Agent Reasoning
- ICLR 2026Best-of-Majority: Minimax-Optimal Strategy for Pass@k Inference Scaling
- ICLR 2026Best-of-N through the Smoothing Lens: KL Divergence and Regret Analysis
- ICLR 2026Best-of-three-worlds Analysis for Dueling Bandits with Borda Winner
- ICLR 2026Better Bounds for the Distributed Experts Problem
- ICLR 2026Beyond Spectra: Eigenvector Overlaps in Loss Geometry
- ICLR 2026Block-Sample MAC-Bayes Generalization Bounds
- ICLR 2026Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers
- ICLR 2026Characterizing the Discrete Geometry of ReLU Networks
- ICLR 2026Closed-form $\ell_r$ norm scaling with data for overparameterized linear regression and diagonal linear networks under $\ell_p$ bias
- ICLR 2026Computational Bottlenecks for Denoising Diffusions
- ICLR 2026Computing Equilibrium beyond Unilateral Deviation
- ICLR 2026Dataset Distillation for Memorized Data: Soft Labels can Leak Held-Out Teacher Knowledge
- ICLR 2026Deep-ICE: The first globally optimal algorithm for empirical risk minimization of two-layer maxout and ReLU networks
- ICLR 2026Deterministic Bounds and Random Estimates of Metric Tensors on Neuromanifolds
- ICLR 2026Differentially Private Equilibrium Finding in Polymatrix Games
- ICLR 2026Differentially Private Two-Stage Gradient Descent for Instrumental Variable Regression
- ICLR 2026Diffusion Language Models are Provably Optimal Parallel Samplers
- ICLR 2026Dimension-Free Decision Calibration for Nonlinear Loss Functions
- ICLR 2026Dimension-Free Minimax Rates for Learning Pairwise Interactions in Attention-Style Models
- ICLR 2026Directional Convergence, Benign Overfitting of Gradient Descent in leaky ReLU two-layer Neural Networks
- ICLR 2026Distributed Algorithms for Euclidean Clustering
- ICLR 2026Diverse Dictionary Learning
- ICLR 2026Diversified Multinomial Logit Contextual Bandits
- ICLR 2026Does the Data Processing Inequality Reflect Practice? On the Utility of Low-Level Tasks
- ICLR 2026Does Weak-to-strong Generalization Happen under Spurious Correlations?
- ICLR 2026Dynamical properties of dense associative memory
- ICLR 2026Efficient Adversarial Attacks on High-dimensional Offline Bandits
- ICLR 2026Efficient Testing for Correlation Clustering: Improved Algorithms and Optimal Bounds
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FAQ
- How many Theory · learning theory papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 1,350 in total: 86 in 2023, 393 in 2024, 389 in 2025, 482 in 2026.
- How many Theory · learning theory papers are at NeurIPS 2026?
- NeurIPS 2026 has 112 Theory · learning theory papers, versus 106 the year before.
- How many Theory · learning theory papers are at ICLR 2026?
- ICLR 2026 has 200 Theory · learning theory papers, versus 147 the year before.
- How many Theory · learning theory papers are at ICML 2026?
- ICML 2026 has 170 Theory · learning theory papers, versus 132 the year before.
- How many Theory · learning theory papers are at CVPR 2025?
- CVPR 2025 has 4 Theory · learning theory papers, versus 1 the year before.
- Which conference publishes the most Theory · learning theory papers?
- NeurIPS, with 540 papers from 2023 to 2026.