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

1,871 papers, page 3 of 38

101. ICLR 2026Gen-DFL: Decision-Focused Generative Learning for Robust Decision Making
102. ICLR 2026Global Resolution: Optimal Multi-Draft Speculative Sampling via Convex Optimization
103. ICLR 2026Globally aware optimization with resurgence
104. ICLR 2026GlowQ: Group-Shared LOw-Rank Approximation for Quantized LLMs
105. ICLR 2026Gradient Descent with Large Step Sizes: Chaos and Fractal Convergence Region
106. ICLR 2026Gradient-Based Diversity Optimization with Differentiable Top-$k$ Objective
107. ICLR 2026Gradient-Normalized Smoothness for Optimization with Approximate Hessians
108. ICLR 2026Graph-based Nearest Neighbors with Dynamic Updates via Random Walks
109. ICLR 2026Group Representational Position Encoding
110. ICLR 2026Group-Normalized Implicit Value Optimization for Language Models
111. ICLR 2026Grouping Nodes with known Value Differences: A lossless UCT-based Abstraction Algorithm
112. ICLR 2026Guaranteed Simply Connected Mesh Reconstruction from an Unorganized Point Cloud
113. ICLR 2026Half-order Fine-Tuning for Diffusion Model: A Recursive Likelihood Ratio Optimizer
114. ICLR 2026Harmonized Cone for Feasible and Non-conflict Directions in Training Physics-Informed Neural Networks
115. ICLR 2026HiFo-Prompt: Prompting with Hindsight and Foresight for LLM-based Automatic Heuristic Design
116. ICLR 2026High Probability Bounds for Non-Convex Stochastic Optimization with Momentum
117. ICLR 2026High-Probability Bounds for the Last Iterate of Clipped SGD
118. ICLR 2026Hinge Regression Tree: A Newton Method for Oblique Regression Tree Splitting
119. ICLR 2026How does the optimizer implicitly bias the model merging loss landscape?
120. ICLR 2026How hard is learning to cut? Trade-offs and sample complexity
121. ICLR 2026Hyperbolic Aware Minimization: Implicit Bias for Sparsity
122. ICLR 2026IDEAL: Data Equilibrium Adaptation for Multi-Capability Language Model Alignment
123. ICLR 2026Implicit Bias and Loss of Plasticity in Matrix Completion: Depth Promotes Low-Rankness
124. ICLR 2026Implicit Bias of Per-sample Adam on Separable Data: Departure from the Full-batch Regime
125. ICLR 2026Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks
126. ICLR 2026Implicit Inversion turns CLIP into a Decoder
127. ICLR 2026Improved $\ell_{p}$ Regression via Iteratively Reweighted Least Squares
128. ICLR 2026Improved high-dimensional estimation with Langevin dynamics and stochastic weight averaging
129. ICLR 2026Improving Feasibility via Fast Autoencoder-Based Projections
130. ICLR 2026Improving LLM-based Global Optimization with Search Space Partitioning
131. ICLR 2026Improving Online-to-Nonconvex Conversion for Smooth Optimization via Double Optimism
132. ICLR 2026Infinite Horizon Markov Economies
133. ICLR 2026INSTANT: Compressing Gradients and Activations for Resource-Efficient Training
134. ICLR 2026Interactive Learning of Single-Index Models via Stochastic Gradient Descent
135. ICLR 2026Landing with the Score: Riemannian Optimization through Denoising
136. ICLR 2026Language Identification in the Limit with Computational Trace
137. ICLR 2026Larger Datasets Can Be Repeated More: A Theoretical Analysis of Multi-Epoch Scaling in Linear Regression
138. ICLR 2026Learning a Game by Paying the Agents
139. ICLR 2026Learning Admissible Heuristics for A*: Theory and Practice
140. ICLR 2026Learning to Adapt: In-Context Learning Beyond Stationarity
141. ICLR 2026Learning to Answer from Correct Demonstrations
142. ICLR 2026Learning to Recall with Transformers Beyond Orthogonal Embeddings
143. ICLR 2026Learning to Segment for Vehicle Routing Problems
144. ICLR 2026Learning to Solve Orienteering Problem with Time Windows and Variable Profits
145. ICLR 2026LEGACY: A Lightweight Dynamic Gradient Compression Strategy for Distributed Deep Learning
146. ICLR 2026Lifelong Learning with Behavior Consolidation for Vehicle Routing
147. ICLR 2026Lightweight Transformer for EEG Classification via Balanced Signed Graph Algorithm Unrolling
148. ICLR 2026LMask: Learn to Solve Constrained Routing Problems with Lazy Masking
149. ICLR 2026LogART: Pushing the Limit of Efficient Logarithmic Post-Training Quantization
150. ICLR 2026LoRA-S: An Efficient Low Rank Adaptation scheme via Sylvester equation

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.