Inference Acceleration papers, 2023–2026

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.

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

48 papers, page 1 of 1

1. ICLR 2026BBQ: Boosting Quantization Entropy with Bell Box Quantization
2. ICLR 2026Corner Gradient Descent
3. ICLR 2026Dataset Distillation as Pushforward Optimal Quantization
4. ICLR 2026DiCache: Let Diffusion Model Determine Its Own Cache
5. ICLR 2026Diffusion LLMs Can Do Faster-Than-AR Inference via Discrete Diffusion Forcing
6. ICLR 2026Distributionally Robust Linear Regression with Block Lewis Weights
7. ICLR 2026Egalitarian Gradient Descent: A Simple Approach to Accelerated Grokking
8. ICLR 2026Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding
9. ICLR 2026GAS: Improving Discretization of Diffusion ODEs via Generalized Adversarial Solver
10. ICLR 2026NLI : Non-uniform Linear Interpolation Approximation of Nonlinear Operations for Efficient LLMs Inference
11. ICLR 2026OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework
12. ICLR 2026RAPID$^3$: Tri-Level Reinforced Acceleration Policies for Diffusion Transformer
13. ICLR 2026Score Distillation Beyond Acceleration: Generative Modeling from Corrupted Data
14. ICLR 2026SGD with Adaptive Preconditioning: Unified Analysis and Momentum Acceleration
15. ICLR 2026Towards a Universally Transferable Acceleration Method for Density Functional Theory
16. ICLR 2026TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate
17. ICLR 2026Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)
18. ICLR 2025Effective Interplay between Sparsity and Quantization: From Theory to Practice
19. ICLR 2025Elucidating the Preconditioning in Consistency Distillation
20. ICLR 2025Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity
21. ICLR 2025Model Equality Testing: Which Model is this API Serving?
22. ICLR 2025Nesterov acceleration in benignly non-convex landscapes
23. ICLR 2025One Step Diffusion via Shortcut Models
24. ICLR 2025Optimizing $(L_0, L_1)$-Smooth Functions by Gradient Methods
25. ICLR 2025PALMBENCH: A COMPREHENSIVE BENCHMARK OF COMPRESSED LARGE LANGUAGE MODELS ON MOBILE PLATFORMS
26. ICLR 2025PEARL: Parallel Speculative Decoding with Adaptive Draft Length
27. ICLR 2025PFDiff: Training-Free Acceleration of Diffusion Models Combining Past and Future Scores
28. ICLR 2025Progressive distillation induces an implicit curriculum
29. ICLR 2025Quamba: A Post-Training Quantization Recipe for Selective State Space Models
30. ICLR 2025Restructuring Vector Quantization with the Rotation Trick
31. ICLR 2025RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs
32. ICLR 2025SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration
33. ICLR 2025Scaling FP8 training to trillion-token LLMs
34. ICLR 2025SGD with memory: fundamental properties and stochastic acceleration
35. ICLR 2025SVDQuant: Absorbing Outliers by Low-Rank Component for 4-Bit Diffusion Models
36. ICLR 2024Embarrassingly Simple Dataset Distillation
37. ICLR 2024InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning
38. ICLR 2023Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats
39. ICLR 2023Bit-Pruning: A Sparse Multiplication-Less Dot-Product
40. ICLR 2023Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization
41. ICLR 2023EVC: Towards Real-Time Neural Image Compression with Mask Decay
42. ICLR 2023Masked Distillation with Receptive Tokens
43. ICLR 2023Minimum Variance Unbiased N:M Sparsity for the Neural Gradients
44. ICLR 2023MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
45. ICLR 2023On the Convergence of AdaGrad(Norm) on $\mathbb{R}^d$: Beyond Convexity, Non-Asymptotic Rate and Acceleration
46. ICLR 2023PowerQuant: Automorphism Search for Non-Uniform Quantization
47. ICLR 2023Scaffolding a Student to Instill Knowledge
48. ICLR 2023Win: Weight-Decay-Integrated Nesterov Acceleration for Adaptive Gradient Algorithms

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.