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

516 papers, page 7 of 11

301. ICML 2025Scalable Model Merging with Progressive Layer-wise Distillation
302. ICML 2025Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
303. ICML 2025Scaling Inference-Efficient Language Models
304. ICML 2025Scaling Laws for Floating–Point Quantization Training
305. ICML 2025Scaling Probabilistic Circuits via Monarch Matrices
306. ICML 2025SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
307. ICML 2025SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization
308. ICML 2025Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model
309. ICML 2025Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks
310. ICML 2025SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity
311. ICML 2025SpikF: Spiking Fourier Network for Efficient Long-term Prediction
312. ICML 2025Star Attention: Efficient LLM Inference over Long Sequences
313. ICML 2025SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training
314. ICML 2025TabFlex: Scaling Tabular Learning to Millions with Linear Attention
315. ICML 2025Temporal Query Network for Efficient Multivariate Time Series Forecasting
316. ICML 2025Tensor Decomposition Based Memory-Efficient Incremental Learning
317. ICML 2025The Hidden Joules: Evaluating the Energy Consumption of Vision Backbones for Progress Towards More Efficient Model Inference
318. ICML 2025The Limits of Tractable Marginalization
319. ICML 2025The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning
320. ICML 2025TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
321. ICML 2025TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state
322. ICML 2025Training Deep Learning Models with Norm-Constrained LMOs
323. ICML 2025UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model
324. ICML 2025Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
325. ICML 2025XAttention: Block Sparse Attention with Antidiagonal Scoring
326. ICML 2025xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
327. NeurIPS 2025$\texttt{BetaConform}$: Efficient MAP Estimation of LLM Ensemble Judgment Performance with Prior Transfer
328. NeurIPS 20254DGCPro: Efficient Hierarchical 4D Gaussian Compression for Progressive Volumetric Video Streaming
329. NeurIPS 2025A Stable Whitening Optimizer for Efficient Neural Network Training
330. NeurIPS 2025A Token is Worth over 1,000 Tokens: Efficient Knowledge Distillation through Low-Rank Clone
331. NeurIPS 2025A Unified Framework for Provably Efficient Algorithms to Estimate Shapley Values
332. NeurIPS 2025Accurate and Efficient Low-Rank Model Merging in Core Space
333. NeurIPS 2025Accurate KV Cache Eviction via Anchor Direction Projection for Efficient LLM Inference
334. NeurIPS 2025Active Measurement: Efficient Estimation at Scale
335. NeurIPS 2025Active Seriation: Efficient Ordering Recovery with Statistical Guarantees
336. NeurIPS 2025Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference
337. NeurIPS 2025AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders
338. NeurIPS 2025All You Need is One: Capsule Prompt Tuning with a Single Vector
339. NeurIPS 2025AmorLIP: Efficient Language-Image Pretraining via Amortization
340. NeurIPS 2025An Efficient Local Search Approach for Polarized Community Discovery in Signed Networks
341. NeurIPS 2025Angles Don’t Lie: Unlocking Training‑Efficient RL Through the Model’s Own Signals
342. NeurIPS 2025Are Language Models Efficient Reasoners? A Perspective from Logic Programming
343. NeurIPS 2025Audits Under Resource, Data, and Access Constraints: Scaling Laws For Less Discriminatory Alternatives
344. NeurIPS 2025Bilevel ZOFO: Efficient LLM Fine-Tuning and Meta-Training
345. NeurIPS 2025Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression
346. NeurIPS 2025CAT: Circular-Convolutional Attention for Sub-Quadratic Transformers
347. NeurIPS 2025Causal Spatio-Temporal Prediction: An Effective and Efficient Multi-Modal Approach
348. NeurIPS 2025ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference
349. NeurIPS 2025COALA: Numerically Stable and Efficient Framework for Context-Aware Low-Rank Approximation
350. NeurIPS 2025CodeGEMM: A Codebook-Centric Approach to Efficient GEMM in Quantized LLMs

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.