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

499 papers, page 3 of 10

101. NeurIPS 2026Neural Neural Scaling Laws
102. NeurIPS 2026NGDB-Zoo: Towards Efficient and Scalable Neural Graph Databases Training
103. NeurIPS 2026NIKA: Efficient Neural Video Representation via Structured Latent Diversity
104. NeurIPS 2026Normalized Architectures are Natively 4-Bit
105. NeurIPS 2026NoTA: Normalized Tensor Adaptation for Parameter-Efficient Continual Learning
106. NeurIPS 2026Omni-Safety under Cross-Modality Conflict: Vulnerabilities, Dynamic Mechanisms and Efficient Alignment
107. NeurIPS 2026OmniSelect: Dynamic Modality-Aware Token Compression for Efficient Omni-modal Large Language Models
108. NeurIPS 2026OmniSpace: Efficient Geometry Awareness for Autonomous Vehicles MLLMs
109. NeurIPS 2026On Minimizing Regret in Fixed-Confidence $\varepsilon$-Best Arm Identification
110. NeurIPS 2026On Neural Scaling Laws for Weather Emulation through Continual Training
111. NeurIPS 2026On the Recall Scaling Laws in Mamba: A Theoretical and Mechanistic Study via Hashing
112. NeurIPS 2026One Temperature to Rule Them All?
113. NeurIPS 2026Optimal and Efficient Contextual Combinatorial Semi-bandits with General Function Approximation
114. NeurIPS 2026Optimal scaling laws in learning hierarchical multi-index models
115. NeurIPS 2026Orlicz–Sobolev with Musielak: An Efficient Regularization Approach for Graph-based IPM
116. NeurIPS 2026Orthros: Phase-Aware Heterogeneous Attention for Efficient Transformers
117. NeurIPS 2026PACE: Pareto-Adaptive Compression for Efficient Native MLLMs
118. NeurIPS 2026Palette: A Modular, Controllable, and Efficient Framework for On-demand Authorized Safety Alignment Relaxation in LLMs
119. NeurIPS 2026Patch Hierarchical Attention Transformers for Efficient Particle Jet Tagging
120. NeurIPS 2026PipeFSDP: Efficient Pipeline Parallel under Fully Sharded Data Parallel for Large Language Model Training
121. NeurIPS 2026Pixels to Tokens: Token Space Efficient Active Learning for Low-Budget Semantic Segmentation
122. NeurIPS 2026Predicting and improving test-time scaling laws via reward tail-guided search
123. NeurIPS 2026Prism Attention: Proposal-Refined Index Sharing Mechanism for Efficient LLMs Inference
124. NeurIPS 2026Progressive Layer-wise Supervision: Deep-to-Shallow Supervision Annealing for Efficient and Robust Speech Deepfake Detection
125. NeurIPS 2026Proper Agnostic Learning of Functions of Halfspaces
126. NeurIPS 2026QueryStop: Dynamic Stop Signals for Efficient Streaming Inference
127. NeurIPS 2026Random Attention Pattern Learning Enables Emergent Capabilities
128. NeurIPS 2026Relaxed On-Policy Distillation: Selective Credit Allocation for Scaling Reasoning Efficiently
129. NeurIPS 2026RelFlexformer: Efficient Attention Transformers for Integrable Relative Positional Encodings
130. NeurIPS 2026RePiD: Efficient Recursive Pixel-Space Diffusion via Hierarchical Patch Denoising
131. NeurIPS 2026Rethinking Dataset Distillation for Classification: Do Distilled Sets Outperform Coresets?
132. NeurIPS 2026Rethinking Expressivity and Efficiency in Test-Time Training
133. NeurIPS 2026Rethinking Infrared Small Target Detection: A Foundation Driven Efficient Paradigm
134. NeurIPS 2026Rich Insights from Cheap Signals: Efficient Evaluations via Tensor Factorization
135. NeurIPS 2026Robust and Efficient Backdoor Mitigation for ML Models via Tolerant Property Testing
136. NeurIPS 2026Robust and Efficient Continual Model Merging via Global Singular Subspace Separation and Restoration
137. NeurIPS 2026ROCKET: Rapid Optimization via Calibration-guided Knapsack-Enhanced Truncation for Efficient Model Compression
138. NeurIPS 2026RubiConv - Efficient Boundary-Respecting Convolutions
139. NeurIPS 2026SageSched: Efficient LLM Scheduling Confronting Demand Uncertainty and Hybridity
140. NeurIPS 2026Sample-Efficient Optimization over Generative Priors via Coarse Learnability
141. NeurIPS 2026Scaling Laws for SAE Training Data
142. NeurIPS 2026Sharp feature-learning transitions and Bayes-optimal neural scaling laws in extensive-width networks
143. NeurIPS 2026Should We Pay This Much for Robustness? Efficient Proxy Certificates with Marginal Guarantees
144. NeurIPS 2026Show Me What You Don’t Know: Efficient Sampling from Invariant Sets for Model Validation
145. NeurIPS 2026SHRED: Retain-Set-Free Unlearning via Self-Distillation with Logit Demotion
146. NeurIPS 2026SimpleEvol: Efficient Intelligence Conversion via Less Human Prior in Automated Heuristic Design
147. NeurIPS 2026SnapMLA: Efficient Long-Context MLA Decoding via Hardware-Aware FP8 Quantized Pipelining
148. NeurIPS 2026SparDA: Sparse Decoupled Attention for Efficient Long-Context LLM Inference
149. NeurIPS 2026Sparse Attention as a Range Searching Problem: Towards an Inference-Efficient Index for KV Cache
150. NeurIPS 2026Speculative Self-Distillation enables Efficient Knowledge Internalization

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.