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

190 papers, page 2 of 4

51. NeurIPS 2025Efficient Fairness-Performance Pareto Front Computation
52. NeurIPS 2025Efficient Hybrid Language Model Compression through Group-Aware SSM Pruning
53. NeurIPS 2025Efficient Kernelized Learning in Polyhedral Games beyond Full Information: From Colonel Blotto to Congestion Games
54. NeurIPS 2025Efficient Large Language Model Inference with Neural Block Linearization
55. NeurIPS 2025Efficient Last-Iterate Convergence in Solving Extensive-Form Games
56. NeurIPS 2025Efficient Multi-bit Quantization Network Training via Weight Bias Correction and Bit-wise Coreset Sampling
57. NeurIPS 2025Efficient Multi-modal Large Language Models via Progressive Consistency Distillation
58. NeurIPS 2025Efficient Multimodal Dataset Distillation via Generative Models
59. NeurIPS 2025Efficient PAC Learning for Realizable-Statistic Models via Convex Surrogates
60. NeurIPS 2025Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems
61. NeurIPS 2025Efficient Part-level 3D Object Generation via Dual Volume Packing
62. NeurIPS 2025Efficient Prompt Compression with Evaluator Heads for Long-Context Transformer Inference
63. NeurIPS 2025Efficient RAW Image Deblurring with Adaptive Frequency Modulation
64. NeurIPS 2025Efficient Representativeness-Aware Coreset Selection
65. NeurIPS 2025Efficient semantic uncertainty quantification in language models via diversity-steered sampling
66. NeurIPS 2025Efficient Speech Language Modeling via Energy Distance in Continuous Latent Space
67. NeurIPS 2025Efficient Utility-Preserving Machine Unlearning with Implicit Gradient Surgery
68. NeurIPS 2025Efficient Verified Unlearning For Distillation
69. NeurIPS 2025ElliCE: Efficient and Provably Robust Algorithmic Recourse via the Rashomon Sets
70. NeurIPS 2025Emergence and scaling laws in SGD learning of shallow neural networks
71. NeurIPS 2025EventMG: Efficient Multilevel Mamba-Graph Learning for Spatiotemporal Event Representation
72. NeurIPS 2025Every Rollout Counts: Optimal Resource Allocation for Efficient Test-Time Scaling
73. NeurIPS 2025F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
74. NeurIPS 2025FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation
75. NeurIPS 2025Fair Minimum Labeling: Efficient Temporal Network Activations for Reachability and Equity
76. NeurIPS 2025FastLongSpeech: Enhancing Large Speech-Language Models for Efficient Long-Speech Processing
77. NeurIPS 2025FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
78. NeurIPS 2025First Attentions Last: Better Exploiting First Attentions for Efficient Parallel Training
79. NeurIPS 2025FlashBias: Fast Computation of Attention with Bias
80. NeurIPS 2025FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts
81. NeurIPS 2025FraPPE: Fast and Efficient Preference-Based Pure Exploration
82. NeurIPS 2025Frequency-Aware Token Reduction for Efficient Vision Transformer
83. NeurIPS 2025Functional Scaling Laws in Kernel Regression: Loss Dynamics and Learning Rate Schedules
84. NeurIPS 2025GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights
85. NeurIPS 2025Gemstones: A Model Suite for Multi-Faceted Scaling Laws
86. NeurIPS 2025Generalized Linear Bandits: Almost Optimal Regret with One-Pass Update
87. NeurIPS 2025Geometry Meets Incentives: Sample-Efficient Incentivized Exploration with Linear Contexts
88. NeurIPS 2025GMV: A Unified and Efficient Graph Multi-View Learning Framework
89. NeurIPS 2025Gradient Multi-Normalization for Efficient LLM Training
90. NeurIPS 2025Group-Level Data Selection for Efficient Pretraining
91. NeurIPS 2025GSPN-2: Efficient Parallel Sequence Modeling
92. NeurIPS 2025Hadamard Test is Sufficient for Efficient Quantum Gradient Estimation with Lie Algebraic Symmetries
93. NeurIPS 2025Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning
94. NeurIPS 2025Hierachical Balance Packing: Towards Efficient Supervised Fine-tuning for Long-Context LLM
95. NeurIPS 2025HiFC: High-efficiency Flash-based KV Cache Swapping for Scaling LLM Inference
96. NeurIPS 2025HollowFlow: Efficient Sample Likelihood Evaluation using Hollow Message Passing
97. NeurIPS 2025Hybrid Re-matching for Continual Learning with Parameter-Efficient Tuning
98. NeurIPS 2025HybridNorm: Towards Stable and Efficient Transformer Training via Hybrid Normalization
99. NeurIPS 2025Hyperbolic Dataset Distillation
100. NeurIPS 2025HyperET: Efficient Training in Hyperbolic Space for Multi-modal Large Language Models

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.