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 8 of 10

351. NeurIPS 2025SubTrack++ : Gradient Subspace Tracking for Scalable LLM Training
352. NeurIPS 2025SUMO: Subspace-Aware Moment-Orthogonalization for Accelerating Memory-Efficient LLM Training
353. NeurIPS 2025Superposition Yields Robust Neural Scaling
354. NeurIPS 2025SymMaP: Improving Computational Efficiency in Linear Solvers through Symbolic Preconditioning
355. NeurIPS 2025Synergy Between the Strong and the Weak: Spiking Neural Networks are Inherently Self-Distillers
356. NeurIPS 2025Teaching Transformers to Solve Combinatorial Problems through Efficient Trial & Error
357. NeurIPS 2025Technical Debt in In-Context Learning: Diminishing Efficiency in Long Context
358. NeurIPS 2025The Omni-Expert: A Computationally Efficient Approach to Achieve a Mixture of Experts in a Single Expert Model
359. NeurIPS 2025Tiled Flash Linear Attention: More Efficient Linear RNN and xLSTM Kernels
360. NeurIPS 2025Towards Interpretable and Efficient Attention: Compressing All by Contracting a Few
361. NeurIPS 2025TrajMamba: An Efficient and Semantic-rich Vehicle Trajectory Pre-training Model
362. NeurIPS 2025UMoE: Unifying Attention and FFN with Shared Experts
363. NeurIPS 2025Unified Scaling Laws for Compressed Representations
364. NeurIPS 2025V2V: Scaling Event-Based Vision through Efficient Video-to-Voxel Simulation
365. NeurIPS 2025Venus-MAXWELL: Efficient Learning of Protein-Mutation Stability Landscapes using Protein Language Models
366. NeurIPS 2025Zebra-Llama: Towards Extremely Efficient Hybrid Models
367. NeurIPS 2025ZeroS: Zero‑Sum Linear Attention for Efficient Transformers
368. NeurIPS 2024$\texttt{dattri}$: A Library for Efficient Data Attribution
369. NeurIPS 2024A Label is Worth A Thousand Images in Dataset Distillation
370. NeurIPS 2024AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment
371. NeurIPS 2024BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts
372. NeurIPS 2024DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking
373. NeurIPS 2024E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation
374. NeurIPS 2024Efficient Convex Algorithms for Universal Kernel Learning
375. NeurIPS 2024FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Discrepancy-Aware Aggregation
376. NeurIPS 2024Genetic-guided GFlowNets for Sample Efficient Molecular Optimization
377. NeurIPS 2024LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment
378. NeurIPS 2024LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing
379. NeurIPS 2024Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
380. NeurIPS 2024Provable and Efficient Dataset Distillation for Kernel Ridge Regression
381. NeurIPS 2024Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching
382. NeurIPS 2024Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies
383. NeurIPS 2024Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
384. NeurIPS 2024SLTrain: a sparse plus low rank approach for parameter and memory efficient pretraining
385. NeurIPS 2024SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead
386. NeurIPS 2024TorchOpt: An Efficient Library for Differentiable Optimization
387. NeurIPS 2024V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark
388. NeurIPS 2023A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting
389. NeurIPS 2023A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design
390. NeurIPS 2023A Smooth Binary Mechanism for Efficient Private Continual Observation
391. NeurIPS 2023Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation
392. NeurIPS 2023Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice
393. NeurIPS 2023Adversarial Training from Mean Field Perspective
394. NeurIPS 2023Alternating Updates for Efficient Transformers
395. NeurIPS 2023Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs
396. NeurIPS 2023An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint
397. NeurIPS 2023An Efficient End-to-End Training Approach for Zero-Shot Human-AI Coordination
398. NeurIPS 2023An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations
399. NeurIPS 2023An Inverse Scaling Law for CLIP Training
400. NeurIPS 2023ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation

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.