Efficient Training papers, 2023–2026

Key findings

• Efficient Training went from 346 papers in 2023 to 603 in 2026, roughly 1.7x in three years.
• NeurIPS publishes the most Efficient Training work: 499 papers from 2023 to 2026, 28% of the four-venue total.
• The fastest-growing overlap is with Deep learning · large language models: papers tagged with both rose from 6 in 2023 to 50 in 2026.
• Among the 5 topics under Efficiency and Systems, it ranks #3 by 2026 paper count; the fastest grower in the group, Hardware-Aware ML, is up 4.4x versus 1.7x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Adaptive Residual Quantization for Memory-Efficient Temporal Action Segmentation
• ICML 2026A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
• ICLR 2026An Efficient SE(p)-Invariant Transport Metric Driven by Polar Transport Discrepancy-based Representation
• CVPR 2026A Bit is All You Need Efficient Video Capture via
• NeurIPS 20254DGCPro: Efficient Hierarchical 4D Gaussian Compression for Progressive Volumetric Video Streaming
• ICML 2025A Sample Efficient Conditional Independence Test in the Presence of Discretization
• ICLR 2025Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator
• CVPR 2025Accurate Scene Text Recognition with Efficient Model Scaling and Cloze Self-Distillation
• NeurIPS 2024$\texttt{dattri}$: A Library for Efficient Data Attribution
• ICML 2024A fast algorithm to simulate nonlinear resistive networks
• ICLR 2024Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks
• CVPR 2024Deep-TROJ: An Inference Stage Trojan Insertion Algorithm through Efficient Weight Replacement Attack
• NeurIPS 2023Alternating Updates for Efficient Transformers
• ICML 2023Auxiliary Modality Learning with Generalized Curriculum Distillation
• ICLR 2023A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning
• CVPR 2023A Rotation-Translation-Decoupled Solution for Robust and Efficient Visual-Inertial Initialization
• NeurIPS 2026Advanced Routing as Regularization Allocation for Efficient Diffusion Transformer Training
• ICML 2026Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance
• ICLR 2026AQER: A Scalable and Efficient Data Loader for Digital Quantum Computers
• CVPR 2026Adaptive Bayesian Early-Exit Networks for Efficient Non-Transferable Learning

All Efficient Training papers

346 papers, page 5 of 7

201. ICML 2023NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning
202. ICML 2023On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm
203. ICML 2023Optimal Rates and Efficient Algorithms for Online Bayesian Persuasion
204. ICML 2023Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks
205. ICML 2023Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
206. ICML 2023PreNAS: Preferred One-Shot Learning Towards Efficient Neural Architecture Search
207. ICML 2023Probabilistic Categorical Adversarial Attack and Adversarial Training
208. ICML 2023Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning
209. ICML 2023Provable Data Subset Selection For Efficient Neural Networks Training
210. ICML 2023Provably and Practically Efficient Neural Contextual Bandits
211. ICML 2023Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs
212. ICML 2023Revisiting Data-Free Knowledge Distillation with Poisoned Teachers
213. ICML 2023Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch
214. ICML 2023Scaling Laws for Multilingual Neural Machine Translation
215. ICML 2023Scaling Spherical CNNs
216. ICML 2023Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory
217. ICML 2023Semiparametrically Efficient Off-Policy Evaluation in Linear Markov Decision Processes
218. ICML 2023Simple Hardware-Efficient Long Convolutions for Sequence Modeling
219. ICML 2023Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability
220. ICML 2023SLAMB: Accelerated Large Batch Training with Sparse Communication
221. ICML 2023SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
222. ICML 2023SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge
223. ICML 2023SpotEM: Efficient Video Search for Episodic Memory
224. ICML 2023Stabilizing GANs' Training with Brownian Motion Controller
225. ICML 2023SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient
226. ICML 2023TAN Without a Burn: Scaling Laws of DP-SGD
227. ICML 2023The case for 4-bit precision: k-bit Inference Scaling Laws
228. ICML 2023Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks
229. ICML 2023Towards Understanding and Improving GFlowNet Training
230. ICML 2023Training Normalizing Flows from Dependent Data
231. ICML 2023Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias
232. ICML 2023Unit Scaling: Out-of-the-Box Low-Precision Training
233. ICML 2023Why Is Public Pretraining Necessary for Private Model Training?
234. ICML 2023Why Random Pruning Is All We Need to Start Sparse
235. NeurIPS 2023A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting
236. NeurIPS 2023A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design
237. NeurIPS 2023A Smooth Binary Mechanism for Efficient Private Continual Observation
238. NeurIPS 2023Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation
239. NeurIPS 2023Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice
240. NeurIPS 2023Adversarial Training from Mean Field Perspective
241. NeurIPS 2023Alternating Updates for Efficient Transformers
242. NeurIPS 2023Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs
243. NeurIPS 2023An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint
244. NeurIPS 2023An Efficient End-to-End Training Approach for Zero-Shot Human-AI Coordination
245. NeurIPS 2023An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations
246. NeurIPS 2023An Inverse Scaling Law for CLIP Training
247. NeurIPS 2023ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation
248. NeurIPS 2023Augmentation-Aware Self-Supervision for Data-Efficient GAN Training
249. NeurIPS 2023Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic Segmentation
250. NeurIPS 2023Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization

FAQ

How many Efficient Training papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,765 in total: 346 in 2023, 300 in 2024, 516 in 2025, 603 in 2026.

How many Efficient Training papers are at NeurIPS 2026?

NeurIPS 2026 has 177 Efficient Training papers, versus 190 the year before.

How many Efficient Training papers are at ICLR 2026?

ICLR 2026 has 148 Efficient Training papers, versus 126 the year before.

How many Efficient Training papers are at ICML 2026?

ICML 2026 has 169 Efficient Training papers, versus 118 the year before.

How many Efficient Training papers are at CVPR 2026?

CVPR 2026 has 109 Efficient Training papers, versus 82 the year before.

Which conference publishes the most Efficient Training papers?

NeurIPS, with 499 papers from 2023 to 2026.