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 23 of 36

1101. NeurIPS 2025Structured Sparse Transition Matrices to Enable State Tracking in State-Space Models
1102. NeurIPS 2025Subspace Networks: Scaling Decentralized Training with Communication-Efficient Model Parallelism
1103. NeurIPS 2025SubTrack++ : Gradient Subspace Tracking for Scalable LLM Training
1104. NeurIPS 2025SUMO: Subspace-Aware Moment-Orthogonalization for Accelerating Memory-Efficient LLM Training
1105. NeurIPS 2025Superposition Yields Robust Neural Scaling
1106. NeurIPS 2025SymMaP: Improving Computational Efficiency in Linear Solvers through Symbolic Preconditioning
1107. NeurIPS 2025Synergy Between the Strong and the Weak: Spiking Neural Networks are Inherently Self-Distillers
1108. NeurIPS 2025Teaching Transformers to Solve Combinatorial Problems through Efficient Trial & Error
1109. NeurIPS 2025Technical Debt in In-Context Learning: Diminishing Efficiency in Long Context
1110. NeurIPS 2025The Omni-Expert: A Computationally Efficient Approach to Achieve a Mixture of Experts in a Single Expert Model
1111. NeurIPS 2025Tiled Flash Linear Attention: More Efficient Linear RNN and xLSTM Kernels
1112. NeurIPS 2025Towards Interpretable and Efficient Attention: Compressing All by Contracting a Few
1113. NeurIPS 2025TrajMamba: An Efficient and Semantic-rich Vehicle Trajectory Pre-training Model
1114. NeurIPS 2025UMoE: Unifying Attention and FFN with Shared Experts
1115. NeurIPS 2025Unified Scaling Laws for Compressed Representations
1116. NeurIPS 2025V2V: Scaling Event-Based Vision through Efficient Video-to-Voxel Simulation
1117. NeurIPS 2025Venus-MAXWELL: Efficient Learning of Protein-Mutation Stability Landscapes using Protein Language Models
1118. NeurIPS 2025Zebra-Llama: Towards Extremely Efficient Hybrid Models
1119. NeurIPS 2025ZeroS: Zero‑Sum Linear Attention for Efficient Transformers
1120. CVPR 20243DGStream: On-the-Fly Training of 3D Gaussians for Efficient Streaming of Photo-Realistic Free-Viewpoint Videos
1121. CVPR 2024A General and Efficient Training for Transformer via Token Expansion
1122. CVPR 2024A Simple Baseline for Efficient Hand Mesh Reconstruction
1123. CVPR 2024Adversarial Score Distillation: When score distillation meets GAN
1124. CVPR 2024ALGM: Adaptive Local-then-Global Token Merging for Efficient Semantic Segmentation with Plain Vision Transformers
1125. CVPR 2024An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning
1126. CVPR 2024Are Conventional SNNs Really Efficient? A Perspective from Network Quantization
1127. CVPR 2024Boosting Image Quality Assessment through Efficient Transformer Adaptation with Local Feature Enhancement
1128. CVPR 2024CHAIN: Enhancing Generalization in Data-Efficient GANs via lipsCHitz continuity constrAIned Normalization
1129. CVPR 2024Characteristics Matching Based Hash Codes Generation for Efficient Fine-grained Image Retrieval
1130. CVPR 2024Circuit Design and Efficient Simulation of Quantum Inner Product and Empirical Studies of Its Effect on Near-Term Hybrid Quantum-Classic Machine Learning
1131. CVPR 2024CLIP-KD: An Empirical Study of CLIP Model Distillation
1132. CVPR 2024Communication-Efficient Collaborative Perception via Information Filling with Codebook
1133. CVPR 2024Communication-Efficient Federated Learning with Accelerated Client Gradient
1134. CVPR 2024Data-Efficient Multimodal Fusion on a Single GPU
1135. CVPR 2024Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images
1136. CVPR 2024Deep-TROJ: An Inference Stage Trojan Insertion Algorithm through Efficient Weight Replacement Attack
1137. CVPR 2024Distilling Semantic Priors from SAM to Efficient Image Restoration Models
1138. CVPR 2024ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt Tuning
1139. CVPR 2024Efficient 3D Implicit Head Avatar with Mesh-anchored Hash Table Blendshapes
1140. CVPR 2024Efficient and Effective Weakly-Supervised Action Segmentation via Action-Transition-Aware Boundary Alignment
1141. CVPR 2024Efficient Hyperparameter Optimization with Adaptive Fidelity Identification
1142. CVPR 2024Efficient Meshflow and Optical Flow Estimation from Event Cameras
1143. CVPR 2024Efficient Model Stealing Defense with Noise Transition Matrix
1144. CVPR 2024Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion Deblurring
1145. CVPR 2024Efficient Multitask Dense Predictor via Binarization
1146. CVPR 2024Efficient Privacy-Preserving Visual Localization Using 3D Ray Clouds
1147. CVPR 2024Efficient Scene Recovery Using Luminous Flux Prior
1148. CVPR 2024Efficient Solution of Point-Line Absolute Pose
1149. CVPR 2024Efficient Stitchable Task Adaptation
1150. CVPR 2024EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation

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.