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

118 papers, page 2 of 3

51. ICML 2025FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation
52. ICML 2025GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration
53. ICML 2025H-Tuning: Toward Low-Cost and Efficient ECG-based Cardiovascular Disease Detection with Pre-Trained Models
54. ICML 2025HiRemate: Hierarchical Approach for Efficient Re-materialization of Neural Networks
55. ICML 2025How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies
56. ICML 2025IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
57. ICML 2025Improved and Oracle-Efficient Online $\ell_1$-Multicalibration
58. ICML 2025Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers
59. ICML 2025Info-Coevolution: An Efficient Framework for Data Model Coevolution
60. ICML 2025Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient
61. ICML 2025KVTuner: Sensitivity-Aware Layer-Wise Mixed-Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference
62. ICML 2025LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
63. ICML 2025Learning from Loss Landscape: Generalizable Mixed-Precision Quantization via Adaptive Sharpness-Aware Gradient Aligning
64. ICML 2025Learning Soft Sparse Shapes for Efficient Time-Series Classification
65. ICML 2025LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
66. ICML 2025Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
67. ICML 2025Memory Layers at Scale
68. ICML 2025MERGE$^3$: Efficient Evolutionary Merging on Consumer-grade GPUs
69. ICML 2025Mixture of Hidden-Dimensions: Not All Hidden-States’ Dimensions are Needed in Transformer
70. ICML 2025Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws
71. ICML 2025Nonparametric Modern Hopfield Models
72. ICML 2025Occult: Optimizing Collaborative Communications across Experts for Accelerated Parallel MoE Training and Inference
73. ICML 2025Olica: Efficient Structured Pruning of Large Language Models without Retraining
74. ICML 2025On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
75. ICML 2025On the Duality between Gradient Transformations and Adapters
76. ICML 2025On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving
77. ICML 2025One Leaf Reveals the Season: Occlusion-Based Contrastive Learning with Semantic-Aware Views for Efficient Visual Representation
78. ICML 2025OrthoRank: Token Selection via Sink Token Orthogonality for Efficient LLM inference
79. ICML 2025Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling
80. ICML 2025Parameter-Efficient Fine-Tuning of State Space Models
81. ICML 2025Position: Enough of Scaling LLMs! Lets Focus on Downscaling
82. ICML 2025Predictive Data Selection: The Data That Predicts Is the Data That Teaches
83. ICML 2025Primphormer: Efficient Graph Transformers with Primal Representations
84. ICML 2025ProofAug: Efficient Neural Theorem Proving via Fine-grained Proof Structure Analysis
85. ICML 2025QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration
86. ICML 2025Reliable and Efficient Amortized Model-based Evaluation
87. ICML 2025Residual Matrix Transformers: Scaling the Size of the Residual Stream
88. ICML 2025Reward-Guided Speculative Decoding for Efficient LLM Reasoning
89. ICML 2025Robust Consensus Anchor Learning for Efficient Multi-view Subspace Clustering
90. ICML 2025RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
91. ICML 2025SageAttention2: Efficient Attention with Thorough Outlier Smoothing and Per-thread INT4 Quantization
92. ICML 2025Sample Efficient Demonstration Selection for In-Context Learning
93. ICML 2025Scalable Model Merging with Progressive Layer-wise Distillation
94. ICML 2025Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
95. ICML 2025Scaling Inference-Efficient Language Models
96. ICML 2025Scaling Laws for Floating–Point Quantization Training
97. ICML 2025Scaling Probabilistic Circuits via Monarch Matrices
98. ICML 2025SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
99. ICML 2025SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization
100. ICML 2025Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model

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.