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

603 papers, page 6 of 13

251. ICLR 2026VQ-Transplant: Efficient VQ-Module Integration for Pre-trained Visual Tokenizers
252. ICLR 2026What Scales in Cross-Entropy Scaling Law?
253. ICLR 2026Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs
254. ICLR 2026WINA: Weight Informed Neuron Activation for Accelerating Large Language Model Inference
255. ICLR 2026xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
256. ICLR 2026Your VAR Model is Secretly an Efficient and Explainable Generative Classifier
257. ICLR 2026ZeroSiam: An Efficient Siamese for Test-Time Entropy Optimization without Collapse
258. ICML 2026(1D) Ordered Tokens Enable Efficient Test-Time Search
259. ICML 2026$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
260. ICML 2026A Bi-metric Framework for Efficient Nearest Neighbor Search
261. ICML 2026A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
262. ICML 2026A Provable Expressiveness Hierarchy in Hybrid Linear-Full Attention
263. ICML 2026A Semantically Consistent Dataset for Data-Efficient Query-Based Universal Sound Separation
264. ICML 2026Accelerating Langevin Monte Carlo via Efficient Stochastic Runge-Kutta Methods beyond Log-Concavity
265. ICML 2026Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
266. ICML 2026Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance
267. ICML 2026AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs
268. ICML 2026An Information-Theoretic Criterion for Efficient Data Synthesis
269. ICML 2026Artificial Hippocampus Networks for Efficient Long-Context Modeling
270. ICML 2026ASTRA: Communication-Efficient Acceleration for Multi-Device Transformer Inference
271. ICML 2026Attributed Network Alignment: Statistical Limits and Efficient Algorithm
272. ICML 2026Beyond Pixels: Mining Compressed Domain Artifacts for Efficient AI-Generated Video Detection
273. ICML 2026Beyond Sunk Costs: Boosting LLM Pre-training Efficiency via Orthogonal Growth of Mixture-of-Experts
274. ICML 2026BiCrossNet with Decoupled Dual Generators: A Parameter‑Efficient and Generalizable Few‑Shot Custom Gesture Recognition Framework
275. ICML 2026BioToken and BioFM – Biologically-Informed Tokenization Enables Accurate and Efficient Genomic Foundation Models
276. ICML 2026Bounded Hyperbolic Tangent: A Stable and Efficient Alternative to Pre-Layer Normalization in Large Language Models
277. ICML 2026Byte Pair Encoding for Efficient Time Series Forecasting
278. ICML 2026Capacity-Aware Mixture Law Enables Efficient LLM Data Optimization
279. ICML 2026CAT-Q: Cost-efficient and Accurate Ternary Quantization for LLMs
280. ICML 2026CauchyNet: Compact and Data-Efficient Learning using Holomorphic Activation Functions
281. ICML 2026Compact Conformal Subgraphs
282. ICML 2026Computationally-efficient Graph Modeling with Refined Graph Random Features
283. ICML 2026Convolutional Learnable-Group Weightless Neural Network
284. ICML 2026Curriculum-Guided Layer Scaling for Language Model Pretraining
285. ICML 2026CurvZO: Adaptive Curvature-Guided Sparse Zeroth-Order Optimization for Efficient LLM Fine-Tuning
286. ICML 2026DASH: Faster Shampoo via Batched Block Preconditioning and Efficient Inverse-Root Solvers
287. ICML 2026Delayed Momentum Aggregation: Communication-efficient Byzantine-robust Federated Learning with Partial Participation
288. ICML 2026Detecting the Semantic Fixed Point: A Geometric Framework for Efficient Inference
289. ICML 2026Dissecting Quantization Error: A Concentration-Alignment Perspective
290. ICML 2026Do Transformers Need Three Projections? Systematic Study of QKV Variants
291. ICML 2026Don't Drop Dropout: Optimizing Layer Sparsity for Efficient LLM Training and Inference
292. ICML 2026Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos
293. ICML 2026Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues
294. ICML 2026EchoAttention: Exploiting Token-Pair Redundancy and Frame-Block Similarity for Efficient Video Generation
295. ICML 2026Effective Distillation to Hybrid xLSTM Architectures
296. ICML 2026Effective MoE-based LLM Compression by Exploiting Heterogeneous Inter-Group Experts Routing Frequency and Information Density
297. ICML 2026Efficient Bayesian Inference from Noisy Pairwise Comparisons
298. ICML 2026Efficient Bilevel Optimization for CKA-Guided MoE Upcycling
299. ICML 2026Efficient Code Analysis via Graph Representation Learning-Guided Large Language Models
300. ICML 2026Efficient Continuous-Depth Modeling with GRU Equivalents

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.