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

300 papers, page 6 of 6

251. ICML 2024Robust Yet Efficient Conformal Prediction Sets
252. ICML 2024Saliency strikes back: How filtering out high frequencies improves white-box explanations
253. ICML 2024Scalable AI Safety via Doubly-Efficient Debate
254. ICML 2024Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
255. ICML 2024Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training
256. ICML 2024Scaling Down Deep Learning with MNIST-1D
257. ICML 2024Scaling Laws for Fine-Grained Mixture of Experts
258. ICML 2024Scaling Laws for the Value of Individual Data Points in Machine Learning
259. ICML 2024See More Details: Efficient Image Super-Resolution by Experts Mining
260. ICML 2024Selecting Large Language Model to Fine-tune via Rectified Scaling Law
261. ICML 2024SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching
262. ICML 2024Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences
263. ICML 2024Simple linear attention language models balance the recall-throughput tradeoff
264. ICML 2024SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization
265. ICML 2024SparQ Attention: Bandwidth-Efficient LLM Inference
266. ICML 2024Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting
267. ICML 2024SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
268. ICML 2024Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC
269. ICML 2024Tandem Transformers for Inference Efficient LLMs
270. ICML 2024Towards efficient deep spiking neural networks construction with spiking activity based pruning
271. ICML 2024Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration
272. ICML 2024Towards Efficient Training and Evaluation of Robust Models against $l_0$ Bounded Adversarial Perturbations
273. ICML 2024Trainable Transformer in Transformer
274. ICML 2024Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
275. ICML 2024Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning
276. ICML 2024TroVE: Inducing Verifiable and Efficient Toolboxes for Solving Programmatic Tasks
277. ICML 2024Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention
278. ICML 2024Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
279. ICML 2024What is Dataset Distillation Learning?
280. ICML 2024When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
281. NeurIPS 2024$\texttt{dattri}$: A Library for Efficient Data Attribution
282. NeurIPS 2024A Label is Worth A Thousand Images in Dataset Distillation
283. NeurIPS 2024AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment
284. NeurIPS 2024BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts
285. NeurIPS 2024DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking
286. NeurIPS 2024E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation
287. NeurIPS 2024Efficient Convex Algorithms for Universal Kernel Learning
288. NeurIPS 2024FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Discrepancy-Aware Aggregation
289. NeurIPS 2024Genetic-guided GFlowNets for Sample Efficient Molecular Optimization
290. NeurIPS 2024LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment
291. NeurIPS 2024LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing
292. NeurIPS 2024Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
293. NeurIPS 2024Provable and Efficient Dataset Distillation for Kernel Ridge Regression
294. NeurIPS 2024Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching
295. NeurIPS 2024Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies
296. NeurIPS 2024Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
297. NeurIPS 2024SLTrain: a sparse plus low rank approach for parameter and memory efficient pretraining
298. NeurIPS 2024SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead
299. NeurIPS 2024TorchOpt: An Efficient Library for Differentiable Optimization
300. NeurIPS 2024V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark

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.