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

1,765 papers, page 34 of 36

1651. ICML 2023Unit Scaling: Out-of-the-Box Low-Precision Training
1652. ICML 2023Why Is Public Pretraining Necessary for Private Model Training?
1653. ICML 2023Why Random Pruning Is All We Need to Start Sparse
1654. NeurIPS 2023A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting
1655. NeurIPS 2023A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design
1656. NeurIPS 2023A Smooth Binary Mechanism for Efficient Private Continual Observation
1657. NeurIPS 2023Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation
1658. NeurIPS 2023Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice
1659. NeurIPS 2023Adversarial Training from Mean Field Perspective
1660. NeurIPS 2023Alternating Updates for Efficient Transformers
1661. NeurIPS 2023Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs
1662. NeurIPS 2023An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint
1663. NeurIPS 2023An Efficient End-to-End Training Approach for Zero-Shot Human-AI Coordination
1664. NeurIPS 2023An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations
1665. NeurIPS 2023An Inverse Scaling Law for CLIP Training
1666. NeurIPS 2023ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation
1667. NeurIPS 2023Augmentation-Aware Self-Supervision for Data-Efficient GAN Training
1668. NeurIPS 2023Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic Segmentation
1669. NeurIPS 2023Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization
1670. NeurIPS 2023Birder: Communication-Efficient 1-bit Adaptive Optimizer for Practical Distributed DNN Training
1671. NeurIPS 2023Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning
1672. NeurIPS 2023Clustering the Sketch: Dynamic Compression for Embedding Tables
1673. NeurIPS 2023Composing Parameter-Efficient Modules with Arithmetic Operation
1674. NeurIPS 2023Connecting Certified and Adversarial Training
1675. NeurIPS 2023Coordinating Distributed Example Orders for Provably Accelerated Training
1676. NeurIPS 2023CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference
1677. NeurIPS 2023Data Portraits: Recording Foundation Model Training Data
1678. NeurIPS 2023Data Pruning via Moving-one-Sample-out
1679. NeurIPS 2023Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training
1680. NeurIPS 2023DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries
1681. NeurIPS 2023Direct Training of SNN using Local Zeroth Order Method
1682. NeurIPS 2023Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training
1683. NeurIPS 2023Does a sparse ReLU network training problem always admit an optimum ?
1684. NeurIPS 2023Don’t just prune by magnitude! Your mask topology is a secret weapon
1685. NeurIPS 2023DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
1686. NeurIPS 2023Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers
1687. NeurIPS 2023Efficient Activation Function Optimization through Surrogate Modeling
1688. NeurIPS 2023Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection
1689. NeurIPS 2023Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards
1690. NeurIPS 2023Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination
1691. NeurIPS 2023Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks
1692. NeurIPS 2023Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks
1693. NeurIPS 2023Efficient Learning of Linear Graph Neural Networks via Node Subsampling
1694. NeurIPS 2023Efficient Online Clustering with Moving Costs
1695. NeurIPS 2023Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs
1696. NeurIPS 2023Efficient Subgame Refinement for Extensive-form Games
1697. NeurIPS 2023Efficient Testable Learning of Halfspaces with Adversarial Label Noise
1698. NeurIPS 2023Efficient Training of Energy-Based Models Using Jarzynski Equality
1699. NeurIPS 2023EgoDistill: Egocentric Head Motion Distillation for Efficient Video Understanding
1700. NeurIPS 2023Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization

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.