Theory · optimization papers, 2023–2026

Key findings

• Theory · optimization went from 123 papers in 2023 to 584 in 2026, roughly 4.7x in three years.
• NeurIPS publishes the most Theory · optimization work: 778 papers from 2023 to 2026, 42% of the four-venue total.
• The fastest-growing overlap is with Low-Rank Adaptation: papers tagged with both rose from 0 in 2023 to 31 in 2026.
• Among the 5 topics under Theory and Statistics, it ranks #1 by 2026 paper count; the fastest grower in the group, Theory · learning theory, is up 5.6x versus 4.7x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Mechanistic Investigation of Theory of Mind in a Large Language Model
• ICML 2026A Direct Second-Order Method for Solving Two-Player Zero-Sum Games
• ICLR 2026A Convergence Analysis of Adaptive Optimizers under Floating-point Quantization
• CVPR 2026TriSim Tri-Dimensional Similarity Modeling with Extreme Value Theory for False-Negative
• NeurIPS 20253BASiL: An Algorithmic Framework for Sparse plus Low-Rank Compression of LLMs
• ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
• ICLR 2025A Coefficient Makes SVRG Effective
• CVPR 2025Dynamic Stereotype Theory Induced Micro-expression Recognition with Oriented Deformation
• NeurIPS 2024A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem
• ICML 2024A Statistical Theory of Regularization-Based Continual Learning
• ICLR 2024A Discretization Framework for Robust Contextual Stochastic Optimization
• NeurIPS 2023[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
• ICML 2023Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity
• ICLR 2023Adaptive Optimization in the $\infty$-Width Limit
• CVPR 2023Deep Hashing With Minimal-Distance-Separated Hash Centers
• NeurIPS 2026Avoiding Obfuscation with Prover-Estimator Debate
• ICML 2026A General Framework for Dynamic Consistent Submodular Maximization
• ICLR 2026A Memory-Efficient Hierarchical Algorithm for Large-scale Optimal Transport Problems
• CVPR 2026FedAdamom Adaptive Momentum for Improved Generalization in Federated Optimization
• NeurIPS 2025A Beyond-Worst-Case Analysis of Greedy k-means++

All Theory · optimization papers

318 papers, page 5 of 7

201. NeurIPS 2025On the Convergence of Stochastic Smoothed Multi-Level Compositional Gradient Descent Ascent
202. NeurIPS 2025On the Emergence of Linear Analogies in Word Embeddings
203. NeurIPS 2025On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
204. NeurIPS 2025On the Robustness of Transformers against Context Hijacking for Linear Classification
205. NeurIPS 2025On the sample complexity of semi-supervised multi-objective learning
206. NeurIPS 2025On Traceability in $\ell_p$ Stochastic Convex Optimization
207. NeurIPS 2025On Transferring Transferability: Towards a Theory for Size Generalization
208. NeurIPS 2025On Universality Classes of Equivariant Networks
209. NeurIPS 2025Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound
210. NeurIPS 2025Online Multi-Class Selection with Group Fairness Guarantee
211. NeurIPS 2025Online Portfolio Selection with ML Predictions
212. NeurIPS 2025Online Two-Stage Submodular Maximization
213. NeurIPS 2025Opinion Maximization in Social Networks by Modifying Internal Opinions
214. NeurIPS 2025OPTFM: A Scalable Multi-View Graph Transformer for Hierarchical Pre-Training in Combinatorial Optimization
215. NeurIPS 2025Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification
216. NeurIPS 2025Optimality and NP-Hardness of Transformers in Learning Markovian Dynamical Functions
217. NeurIPS 2025Optimistic Online-to-Batch Conversions for Accelerated Convergence and Universality
218. NeurIPS 2025Optimizing the Unknown: Black Box Bayesian Optimization with Energy-Based Model and Reinforcement Learning
219. NeurIPS 2025Oracle-Efficient Combinatorial Semi-Bandits
220. NeurIPS 2025Parameter-free Algorithms for the Stochastically Extended Adversarial Model
221. NeurIPS 2025Partial Correlation Network Estimation by Semismooth Newton Methods
222. NeurIPS 2025Pause Tokens Strictly Increase the Expressivity of Constant-Depth Transformers
223. NeurIPS 2025PaZO: Preconditioned Accelerated Zeroth-Order Optimization for Fine-Tuning LLMs
224. NeurIPS 2025PDPO: Parametric Density Path Optimization
225. NeurIPS 2025Perturbation Bounds for Low-Rank Inverse Approximations under Noise
226. NeurIPS 2025PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts
227. NeurIPS 2025Predictability Enables Parallelization of Nonlinear State Space Models
228. NeurIPS 2025Preference Optimization on Pareto Sets: On a Theory of Multi-Objective Optimization
229. NeurIPS 2025Price of Parsimony: Complexity of Fourier Sparsity Testing
230. NeurIPS 2025Probing Neural Combinatorial Optimization Models
231. NeurIPS 2025Problem-Parameter-Free Decentralized Bilevel Optimization
232. NeurIPS 2025Product Distribution Learning with Imperfect Advice
233. NeurIPS 2025Provable Meta-Learning with Low-Rank Adaptations
234. NeurIPS 2025Purest Quantum State Identification
235. NeurIPS 2025Purity Law for Neural Routing Problem Solvers with Enhanced Generalizability
236. NeurIPS 2025Quantum Speedups for Minimax Optimization and Beyond
237. NeurIPS 2025Quasi-Self-Concordant Optimization with $\ell_{\infty}$ Lewis Weights
238. NeurIPS 2025Reinforcement learning for one-shot DAG scheduling with comparability identification and dense reward
239. NeurIPS 2025Replicable Distribution Testing
240. NeurIPS 2025Replicable Online Learning
241. NeurIPS 2025Rethinking Entropy in Test-Time Adaptation: The Missing Piece from Energy Duality
242. NeurIPS 2025Rethinking Gradient Step Denoiser: Towards Truly Pseudo-Contractive Operator
243. NeurIPS 2025Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees
244. NeurIPS 2025Revisiting 1-peer exponential graph for enhancing decentralized learning efficiency
245. NeurIPS 2025Revisiting Agnostic Boosting
246. NeurIPS 2025Revisiting Consensus Error: A Fine-grained Analysis of Local SGD under Second-order Data Heterogeneity
247. NeurIPS 2025Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems
248. NeurIPS 2025Revisiting Frank-Wolfe for Structured Nonconvex Optimization
249. NeurIPS 2025Robust Federated Finetuning of LLMs via Alternating Optimization of LoRA
250. NeurIPS 2025Robustifying Learning-Augmented Caching Efficiently without Compromising 1-Consistency

FAQ

How many Theory · optimization papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,871 in total: 123 in 2023, 494 in 2024, 670 in 2025, 584 in 2026.

How many Theory · optimization papers are at NeurIPS 2026?

NeurIPS 2026 has 119 Theory · optimization papers, versus 318 the year before.

How many Theory · optimization papers are at ICLR 2026?

ICLR 2026 has 244 Theory · optimization papers, versus 196 the year before.

How many Theory · optimization papers are at ICML 2026?

ICML 2026 has 214 Theory · optimization papers, versus 147 the year before.

How many Theory · optimization papers are at CVPR 2026?

CVPR 2026 has 7 Theory · optimization papers, versus 9 the year before.

Which conference publishes the most Theory · optimization papers?

NeurIPS, with 778 papers from 2023 to 2026.