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

148 papers, page 3 of 3

101. ICLR 2026Out of the Memory Barrier: A Highly Memory-Efficient Training System for LLMs with Million-Token Contexts
102. ICLR 2026ParoQuant: Pairwise Rotation Quantization for Efficient Reasoning LLM Inference
103. ICLR 2026PASER: Post-Training Data Selection for Efficient Pruned Large Language Model Recovery
104. ICLR 2026PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecasting
105. ICLR 2026PiCa: Parameter-Efficient Fine-Tuning with Column Space Projection
106. ICLR 2026Pre-training under infinite compute
107. ICLR 2026ProxyAttn: Guided Sparse Attention via Representative Heads
108. ICLR 2026QKV Projections Require a Fraction of Their Memory
109. ICLR 2026Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization
110. ICLR 2026Quantized Gradient Projection for Memory-Efficient Continual Learning
111. ICLR 2026QuoKA: Query-Oriented KV Selection for Efficient LLM Prefill
112. ICLR 2026RainPro-8: An Efficient Deep Learning Model to Estimate Rainfall Probabilities Over 8 Hours
113. ICLR 2026Remaining-data-free Machine Unlearning by Suppressing Sample Contribution
114. ICLR 2026Rethinking JEPA: Compute‑Efficient Video Self-Supervised Learning with Frozen Teachers
115. ICLR 2026RMAAT: Astrocyte-Inspired Memory Compression and Replay for Efficient Long-Context Transformers
116. ICLR 2026Scalable Random Wavelet Features: Efficient Non-Stationary Kernel Approximation with Convergence Guarantees
117. ICLR 2026Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs
118. ICLR 2026Scaling Laws Revisited: Modeling the Role of Data Quality in Language Model Pretraining
119. ICLR 2026Scaling Up, Speeding Up: A Benchmark of Speculative Decoding for Efficient LLM Test-Time Scaling
120. ICLR 2026Scaling with Collapse: Efficient and Predictable Training of LLM Families
121. ICLR 2026SecP-Tuning: Efficient Privacy-Preserving Prompt Tuning for Large Language Models via MPC
122. ICLR 2026Sem-MoE: Semantic-aware Model-Data Collaborative Scheduling for Efficient MoE Inference
123. ICLR 2026Semantic Voting: A Self-Evaluation-Free Approach for Efficient LLM Self-Improvement on Unverifiable Open-ended Tasks
124. ICLR 2026SERE: Similarity-based Expert Re-routing for Efficient Batch Decoding in MoE Models
125. ICLR 2026SparseEval: Efficient Evaluation of Large Language Models by Sparse Optimization
126. ICLR 2026SPICE: Submodular Penalized Information–Conflict Selection for Efficient Large Language Model Training
127. ICLR 2026SSDi8: Accurate and Efficient 8-bit Quantization for State Space Duality
128. ICLR 2026STaMP: Sequence Transformation and Mixed Precision for Low-Precision Activation Quantization
129. ICLR 2026Stopping Computation for Converged Tokens in Masked Diffusion-LM Decoding
130. ICLR 2026Test-Time Efficient Pretrained Model Portfolios for Time Series Forecasting
131. ICLR 2026TGM: A Modular and Efficient Library for Machine Learning on Temporal Graphs
132. ICLR 2026TokenSeek: Memory Efficient Fine Tuning via Instance-Aware Token Ditching
133. ICLR 2026Towards Greater Leverage: Scaling Laws for Efficient Mixture-of-Experts Language Models
134. ICLR 2026Towards Lossless Memory-efficient Training of Spiking Neural Networks via Gradient Checkpointing and Spike Compression
135. ICLR 2026ULD-Net: Enabling Ultra-Low-Degree Fully Polynomial Networks for Homomorphically Encrypted Inference
136. ICLR 2026UltraMemV2: Memory Networks Scaling to 120B Parameters with Superior Long-Context Learning
137. ICLR 2026UniCon: Unified Framework for Efficient Contrastive Alignment via Kernels
138. ICLR 2026Unified and Efficient Multi-view Clustering from Probabilistic Perspective
139. ICLR 2026Universal Model Routing for Efficient LLM Inference
140. ICLR 2026Unlocking Full Efficiency of Token Filtering in Large Language Model Training
141. ICLR 2026Unveiling Downstream Performance Scaling of LLMs: A Clustering-Based Perspective
142. ICLR 2026VQ-Transplant: Efficient VQ-Module Integration for Pre-trained Visual Tokenizers
143. ICLR 2026What Scales in Cross-Entropy Scaling Law?
144. ICLR 2026Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs
145. ICLR 2026WINA: Weight Informed Neuron Activation for Accelerating Large Language Model Inference
146. ICLR 2026xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
147. ICLR 2026Your VAR Model is Secretly an Efficient and Explainable Generative Classifier
148. ICLR 2026ZeroSiam: An Efficient Siamese for Test-Time Entropy Optimization without Collapse

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.