Inference Acceleration papers, 2023–2026
Quantization, distillation, and serving
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 259 papers are tagged with this topic.
Key findings
- Inference Acceleration went from 54 papers in 2023 to 91 in 2026, roughly 1.7x in three years.
- NeurIPS publishes the most Inference Acceleration work: 90 papers from 2023 to 2026, 35% of the four-venue total.
- The fastest-growing overlap is with Deep learning · large language models: papers tagged with both rose from 1 in 2023 to 9 in 2026.
- Among the 5 topics under Efficiency and Systems, it ranks #5 by 2026 paper count; the fastest grower in the group, Hardware-Aware ML, is up 4.4x versus 1.7x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 20 | 11 | 7 | 16 | 54 |
| 2024 | 22 | 2 | 13 | 13 | 50 |
| 2025 | 15 | 18 | 22 | 9 | 64 |
| 2026 | 33 | 17 | 26 | 15 | 91 |
Representative papers
Spread across years and venues so every edition shows up
- NeurIPS 2026A Method-Class Divide in Sub-4-Bit Quantization:\\Iterative vs.\ Single-Pass Sensitivity to Data Composition
- ICML 2026Consistency Deep Equilibrium Models
- ICLR 2026OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework
- CVPR 2026GeoRK2 Geometry-Guided Runge-Kutta Integration for Diffusion Transformer Acceleration
- NeurIPS 2025PolarQuant: Leveraging Polar Transformation for Key Cache Quantization and Decoding Acceleration
- ICML 2025RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers
- ICLR 2025Progressive distillation induces an implicit curriculum
- CVPR 2025Adapting Dense Matching for Homography Estimation with Grid-based Acceleration
- NeurIPS 2024Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks
- ICML 2024Diversified Batch Selection for Training Acceleration
- ICLR 2024Embarrassingly Simple Dataset Distillation
- CVPR 2024Data-Free Quantization via Pseudo-label Filtering
- NeurIPS 2023Continuous-time Analysis of Anchor Acceleration
- ICML 2023Auxiliary Modality Learning with Generalized Curriculum Distillation
- ICLR 2023Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats
- CVPR 2023NIPQ: Noise Proxy-Based Integrated Pseudo-Quantization
- NeurIPS 2026AcceleGrad#: Adaptive Geometry-Aware Acceleration
- ICML 2026PsumQuant: In-line Post-training Partial Sum Quantizer for Energy Efficient NPU Inference
- ICLR 2026NLI : Non-uniform Linear Interpolation Approximation of Nonlinear Operations for Efficient LLMs Inference
- CVPR 2026SODA Sensitivity-Oriented Dynamic Acceleration for Diffusion Transformer
All Inference Acceleration papers
15 papers, page 1 of 1
- CVPR 2026Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration
- CVPR 2026D2Cache Second-Order Delta Caching for Higher Video Diffusion Acceleration
- CVPR 2026Denoising as Path Planning Training-Free Acceleration of Diffusion Models with
- CVPR 2026Fast3Dcache Training-free 3D Geometry Synthesis Acceleration
- CVPR 2026Flow Map Distillation Without Data
- CVPR 2026GeoRK2 Geometry-Guided Runge-Kutta Integration for Diffusion Transformer Acceleration
- CVPR 2026Just-in-Time Training-Free Spatial Acceleration for Diffusion Transformers
- CVPR 2026LESA Learnable Stage-Aware Predictors for Diffusion Model Acceleration
- CVPR 2026Masked Auto-Regressive Variational Acceleration Fast Inference Makes Practical Reinforcement Learning
- CVPR 2026ResCa Residual Caching for Diffusion Transformers Acceleration
- CVPR 2026S2D Selective Spectral Decay for Quantization-Friendly Conditioning of Neural Activations
- CVPR 2026Seele A Unified Acceleration Framework for Real-Time Gaussian Splatting on
- CVPR 2026SODA Sensitivity-Oriented Dynamic Acceleration for Diffusion Transformer
- CVPR 2026TAP A Token-Adaptive Predictor Framework for Training-Free Diffusion Acceleration
- CVPR 2026TC-Pade Trajectory-Consistent Pade Approximation for Diffusion Acceleration
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FAQ
- How many Inference Acceleration papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 259 in total: 54 in 2023, 50 in 2024, 64 in 2025, 91 in 2026.
- How many Inference Acceleration papers are at NeurIPS 2026?
- NeurIPS 2026 has 33 Inference Acceleration papers, versus 15 the year before.
- How many Inference Acceleration papers are at ICLR 2026?
- ICLR 2026 has 17 Inference Acceleration papers, versus 18 the year before.
- How many Inference Acceleration papers are at ICML 2026?
- ICML 2026 has 26 Inference Acceleration papers, versus 22 the year before.
- How many Inference Acceleration papers are at CVPR 2026?
- CVPR 2026 has 15 Inference Acceleration papers, versus 9 the year before.
- Which conference publishes the most Inference Acceleration papers?
- NeurIPS, with 90 papers from 2023 to 2026.