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 21 of 36

1001. NeurIPS 2025Every Rollout Counts: Optimal Resource Allocation for Efficient Test-Time Scaling
1002. NeurIPS 2025F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
1003. NeurIPS 2025FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation
1004. NeurIPS 2025Fair Minimum Labeling: Efficient Temporal Network Activations for Reachability and Equity
1005. NeurIPS 2025FastLongSpeech: Enhancing Large Speech-Language Models for Efficient Long-Speech Processing
1006. NeurIPS 2025FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
1007. NeurIPS 2025First Attentions Last: Better Exploiting First Attentions for Efficient Parallel Training
1008. NeurIPS 2025FlashBias: Fast Computation of Attention with Bias
1009. NeurIPS 2025FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts
1010. NeurIPS 2025FraPPE: Fast and Efficient Preference-Based Pure Exploration
1011. NeurIPS 2025Frequency-Aware Token Reduction for Efficient Vision Transformer
1012. NeurIPS 2025Functional Scaling Laws in Kernel Regression: Loss Dynamics and Learning Rate Schedules
1013. NeurIPS 2025GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights
1014. NeurIPS 2025Gemstones: A Model Suite for Multi-Faceted Scaling Laws
1015. NeurIPS 2025Generalized Linear Bandits: Almost Optimal Regret with One-Pass Update
1016. NeurIPS 2025Geometry Meets Incentives: Sample-Efficient Incentivized Exploration with Linear Contexts
1017. NeurIPS 2025GMV: A Unified and Efficient Graph Multi-View Learning Framework
1018. NeurIPS 2025Gradient Multi-Normalization for Efficient LLM Training
1019. NeurIPS 2025Group-Level Data Selection for Efficient Pretraining
1020. NeurIPS 2025GSPN-2: Efficient Parallel Sequence Modeling
1021. NeurIPS 2025Hadamard Test is Sufficient for Efficient Quantum Gradient Estimation with Lie Algebraic Symmetries
1022. NeurIPS 2025Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning
1023. NeurIPS 2025Hierachical Balance Packing: Towards Efficient Supervised Fine-tuning for Long-Context LLM
1024. NeurIPS 2025HiFC: High-efficiency Flash-based KV Cache Swapping for Scaling LLM Inference
1025. NeurIPS 2025HollowFlow: Efficient Sample Likelihood Evaluation using Hollow Message Passing
1026. NeurIPS 2025Hybrid Re-matching for Continual Learning with Parameter-Efficient Tuning
1027. NeurIPS 2025HybridNorm: Towards Stable and Efficient Transformer Training via Hybrid Normalization
1028. NeurIPS 2025Hyperbolic Dataset Distillation
1029. NeurIPS 2025HyperET: Efficient Training in Hyperbolic Space for Multi-modal Large Language Models
1030. NeurIPS 2025Implicit-ARAP: Efficient Handle-Guided Neural Field Deformation via Local Patch Meshing
1031. NeurIPS 2025Improved Scaling Laws in Linear Regression via Data Reuse
1032. NeurIPS 2025Improving Decision Trees through the Lens of Parameterized Local Search
1033. NeurIPS 2025InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion
1034. NeurIPS 2025Interpretable and Parameter Efficient Graph Neural Additive Models with Random Fourier Features
1035. NeurIPS 2025Irrational Complex Rotations Empower Low-bit Optimizers
1036. NeurIPS 2025Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search
1037. NeurIPS 2025Kernel Learning with Adversarial Features: Numerical Efficiency and Adaptive Regularization
1038. NeurIPS 2025Layer as Puzzle Pieces: Compressing Large Language Models through Layer Concatenation
1039. NeurIPS 2025Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning
1040. NeurIPS 2025LayerNavigator: Finding Promising Intervention Layers for Efficient Activation Steering in Large Language Models
1041. NeurIPS 2025Learned Prefix Caching for Efficient LLM Inference
1042. NeurIPS 2025Learning in Compact Spaces with Approximately Normalized Transformer
1043. NeurIPS 2025Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
1044. NeurIPS 2025Less Is More, but Where? Dynamic Token Compression via LLM-Guided Keyframe Prior
1045. NeurIPS 2025Linear Attention for Efficient Bidirectional Sequence Modeling
1046. NeurIPS 2025LLM at Network Edge: A Layer-wise Efficient Federated Fine-tuning Approach
1047. NeurIPS 2025LookWhere? Efficient Visual Recognition by Learning Where to Look and What to See from Self-Supervision
1048. NeurIPS 2025LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades
1049. NeurIPS 2025Mamba Modulation: On the Length Generalization of Mamba Models
1050. NeurIPS 2025Mamba Only Glances Once (MOGO): A Lightweight Framework for Efficient Video Action Detection

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.