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 35 of 36

1701. NeurIPS 2023Energy-Efficient Scheduling with Predictions
1702. NeurIPS 2023Explainable and Efficient Randomized Voting Rules
1703. NeurIPS 2023Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks
1704. NeurIPS 2023FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations
1705. NeurIPS 2023Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations
1706. NeurIPS 2023GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients
1707. NeurIPS 2023H3T: Efficient Integration of Memory Optimization and Parallelism for Large-scale Transformer Training
1708. NeurIPS 2023How2comm: Communication-Efficient and Collaboration-Pragmatic Multi-Agent Perception
1709. NeurIPS 2023Hybrid Search for Efficient Planning with Completeness Guarantees
1710. NeurIPS 2023Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency
1711. NeurIPS 2023Language Semantic Graph Guided Data-Efficient Learning
1712. NeurIPS 2023Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations
1713. NeurIPS 2023Mask Propagation for Efficient Video Semantic Segmentation
1714. NeurIPS 2023Maximum Independent Set: Self-Training through Dynamic Programming
1715. NeurIPS 2023MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers
1716. NeurIPS 2023Memory Efficient Optimizers with 4-bit States
1717. NeurIPS 2023MGDD: A Meta Generator for Fast Dataset Distillation
1718. NeurIPS 2023MixFormerV2: Efficient Fully Transformer Tracking
1719. NeurIPS 2023MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining
1720. NeurIPS 2023Multiplication-Free Transformer Training via Piecewise Affine Operations
1721. NeurIPS 2023NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks
1722. NeurIPS 2023Neural Priming for Sample-Efficient Adaptation
1723. NeurIPS 2023NICE: NoIse-modulated Consistency rEgularization for Data-Efficient GANs
1724. NeurIPS 2023No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models
1725. NeurIPS 2023On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes
1726. NeurIPS 2023Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
1727. NeurIPS 2023Patch n’ Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution
1728. NeurIPS 2023PDP: Parameter-free Differentiable Pruning is All You Need
1729. NeurIPS 2023Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources
1730. NeurIPS 2023Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers
1731. NeurIPS 2023Progressive Ensemble Distillation: Building Ensembles for Efficient Inference
1732. NeurIPS 2023QLoRA: Efficient Finetuning of Quantized LLMs
1733. NeurIPS 2023RangePerception: Taming LiDAR Range View for Efficient and Accurate 3D Object Detection
1734. NeurIPS 2023ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation
1735. NeurIPS 2023ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting
1736. NeurIPS 2023RETVec: Resilient and Efficient Text Vectorizer
1737. NeurIPS 2023Reusing Pretrained Models by Multi-linear Operators for Efficient Training
1738. NeurIPS 2023Sample-efficient Multi-objective Molecular Optimization with GFlowNets
1739. NeurIPS 2023ScaleLong: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection
1740. NeurIPS 2023Scaling Data-Constrained Language Models
1741. NeurIPS 2023ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
1742. NeurIPS 2023SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
1743. NeurIPS 2023SLaM: Student-Label Mixing for Distillation with Unlabeled Examples
1744. NeurIPS 2023Slimmed Asymmetrical Contrastive Learning and Cross Distillation for Lightweight Model Training
1745. NeurIPS 2023Softmax Output Approximation for Activation Memory-Efficient Training of Attention-based Networks
1746. NeurIPS 2023Sparse Modular Activation for Efficient Sequence Modeling
1747. NeurIPS 2023SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks
1748. NeurIPS 2023Sparsity-Preserving Differentially Private Training of Large Embedding Models
1749. NeurIPS 2023Speculative Decoding with Big Little Decoder
1750. NeurIPS 2023Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective

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.