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

603 papers, page 11 of 13

501. NeurIPS 2026GramStatTexNet: Efficient, Interpretable, and Neuro-Inspired Texture Analysis-by-Synthesis
502. NeurIPS 2026HetCCL: Efficient LLM Training on Heterogeneous Vendor GPUs
503. NeurIPS 2026HiFloat4 Format for Language Model Pre-training on Ascend NPUs
504. NeurIPS 2026Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization
505. NeurIPS 2026How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models
506. NeurIPS 2026Human-Inspired, Task-Dimension-Guided Exploration for Efficient Learning and Transfer in High Dimensions
507. NeurIPS 2026Hyperbolic Language Models: From Zipf to Compute-Optimal Scaling
508. NeurIPS 2026HyperVAttention: Efficient Sparse Attention with Spatio-Temporal Clustering for Video Diffusion
509. NeurIPS 2026IncAgg: Efficient Memory-Enhanced Graph Learning via Incremental Aggregation
510. NeurIPS 2026Joint Sequence--Vocabulary Selection for Efficient LLM Distillation
511. NeurIPS 2026Label-Efficient Dataset Pruning via Semi-Supervised Pseudo-Labeling
512. NeurIPS 2026Learning to Foresee: Unveiling the Unlocking Efficiency of On-Policy Distillation
513. NeurIPS 2026Leech Lattice Vector Quantization for Efficient LLM Compression
514. NeurIPS 2026LEMON-ZEST: Evolution-Informed Tokenization for Efficient Protein Language Modeling
515. NeurIPS 2026LIME: Link-based User-item Interaction Modeling with Decoupled XOR Attention for Efficient Test Time Scaling
516. NeurIPS 2026LLM Routing Through the Lens of Recommendation: A Roadmap for Efficient AI Orchestration
517. NeurIPS 2026Logical Distillation of Transformer Encoders
518. NeurIPS 2026LoopPrune: Evolutionary Module Selection with Iterative Execution for Efficient Large Language Model Compression
519. NeurIPS 2026Magnitude-preserving Layers Enable Efficient GANs
520. NeurIPS 2026Map-Guided Caching: A Global Perspective for Efficient Diffusion Transformer
521. NeurIPS 2026Matched-Control Tests of Partition-Source Claims in One Routed Distillation Family
522. NeurIPS 2026MemForest: Efficient Agent Memory Management via EventTree Partitioning and Progressive Merging
523. NeurIPS 2026Meta-memorization and memorization scaling laws in transformers
524. NeurIPS 2026MGMem: An Efficient, Deterministic, and Provenance-Preserving Framework for Long-Horizon Agent Memory
525. NeurIPS 2026Mixture-of-Top-$k$ Attention: Efficient Attention as Scalable Fast Weights
526. NeurIPS 2026MoE-SpAc: Efficient MoE Inference Based on Speculative Activation Utility in Heterogeneous Edge Scenario
527. NeurIPS 2026Neural Neural Scaling Laws
528. NeurIPS 2026NGDB-Zoo: Towards Efficient and Scalable Neural Graph Databases Training
529. NeurIPS 2026NIKA: Efficient Neural Video Representation via Structured Latent Diversity
530. NeurIPS 2026Normalized Architectures are Natively 4-Bit
531. NeurIPS 2026NoTA: Normalized Tensor Adaptation for Parameter-Efficient Continual Learning
532. NeurIPS 2026Omni-Safety under Cross-Modality Conflict: Vulnerabilities, Dynamic Mechanisms and Efficient Alignment
533. NeurIPS 2026OmniSelect: Dynamic Modality-Aware Token Compression for Efficient Omni-modal Large Language Models
534. NeurIPS 2026OmniSpace: Efficient Geometry Awareness for Autonomous Vehicles MLLMs
535. NeurIPS 2026On Minimizing Regret in Fixed-Confidence $\varepsilon$-Best Arm Identification
536. NeurIPS 2026On Neural Scaling Laws for Weather Emulation through Continual Training
537. NeurIPS 2026On the Recall Scaling Laws in Mamba: A Theoretical and Mechanistic Study via Hashing
538. NeurIPS 2026One Temperature to Rule Them All?
539. NeurIPS 2026Optimal and Efficient Contextual Combinatorial Semi-bandits with General Function Approximation
540. NeurIPS 2026Optimal scaling laws in learning hierarchical multi-index models
541. NeurIPS 2026Orlicz–Sobolev with Musielak: An Efficient Regularization Approach for Graph-based IPM
542. NeurIPS 2026Orthros: Phase-Aware Heterogeneous Attention for Efficient Transformers
543. NeurIPS 2026PACE: Pareto-Adaptive Compression for Efficient Native MLLMs
544. NeurIPS 2026Palette: A Modular, Controllable, and Efficient Framework for On-demand Authorized Safety Alignment Relaxation in LLMs
545. NeurIPS 2026Patch Hierarchical Attention Transformers for Efficient Particle Jet Tagging
546. NeurIPS 2026PipeFSDP: Efficient Pipeline Parallel under Fully Sharded Data Parallel for Large Language Model Training
547. NeurIPS 2026Pixels to Tokens: Token Space Efficient Active Learning for Low-Budget Semantic Segmentation
548. NeurIPS 2026Predicting and improving test-time scaling laws via reward tail-guided search
549. NeurIPS 2026Prism Attention: Proposal-Refined Index Sharing Mechanism for Efficient LLMs Inference
550. NeurIPS 2026Progressive Layer-wise Supervision: Deep-to-Shallow Supervision Annealing for Efficient and Robust Speech Deepfake 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.