推理加速论文趋势 2023–2026
量化、蒸馏与 serving
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 259 篇被归入该主题的论文。
主要结论
- 推理加速论文从 2023 年的 54 篇增长到 2026 年的 91 篇，三年间扩大到约 1.7 倍。
- NeurIPS 是发推理加速论文最多的会议，2023–2026 年共 90 篇，占四个会议总量的 35%。
- 交叉方向里涨得最快的是深度学习 · large language models：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 9 篇。
- 在「效率与系统」的 5 个主题里，它的 2026 年论文数排第 5；同组增长最快的硬件协同是 4.4 倍，推理加速是 1.7 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 20 | 11 | 7 | 16 | 54 |
| 2024 | 22 | 2 | 13 | 13 | 50 |
| 2025 | 15 | 18 | 22 | 9 | 64 |
| 2026 | 33 | 17 | 26 | 15 | 91 |
代表论文
按年份和会议均匀挑选，方便快速看到每一届的样貌
- 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
全部推理加速论文
共 259 篇，第 5 / 6 页
- NeurIPS 2024ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
- NeurIPS 2024Speculative Decoding with CTC-based Draft Model for LLM Inference Acceleration
- NeurIPS 2024UniFL: Improve Latent Diffusion Model via Unified Feedback Learning
- NeurIPS 2024Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction
- NeurIPS 2024VQ-Map: Bird's-Eye-View Map Layout Estimation in Tokenized Discrete Space via Vector Quantization
- CVPR 2023Adaptive Data-Free Quantization
- CVPR 2023Binary Latent Diffusion
- CVPR 2023Boost Vision Transformer With GPU-Friendly Sparsity and Quantization
- CVPR 2023DepGraph: Towards Any Structural Pruning
- CVPR 2023DistilPose: Tokenized Pose Regression With Heatmap Distillation
- CVPR 2023DisWOT: Student Architecture Search for Distillation WithOut Training
- CVPR 2023Efficient RGB-T Tracking via Cross-Modality Distillation
- CVPR 2023Generic-to-Specific Distillation of Masked Autoencoders
- CVPR 2023Hard Sample Matters a Lot in Zero-Shot Quantization
- CVPR 2023Network Expansion for Practical Training Acceleration
- CVPR 2023NIPQ: Noise Proxy-Based Integrated Pseudo-Quantization
- CVPR 2023On Distillation of Guided Diffusion Models
- CVPR 2023PD-Quant: Post-Training Quantization Based on Prediction Difference Metric
- CVPR 2023Post-Training Quantization on Diffusion Models
- CVPR 2023Practical Network Acceleration With Tiny Sets
- CVPR 2023Solving Oscillation Problem in Post-Training Quantization Through a Theoretical Perspective
- ICLR 2023Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats
- ICLR 2023Bit-Pruning: A Sparse Multiplication-Less Dot-Product
- ICLR 2023Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization
- ICLR 2023EVC: Towards Real-Time Neural Image Compression with Mask Decay
- ICLR 2023Masked Distillation with Receptive Tokens
- ICLR 2023Minimum Variance Unbiased N:M Sparsity for the Neural Gradients
- ICLR 2023MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
- ICLR 2023On the Convergence of AdaGrad(Norm) on $\mathbb{R}^d$: Beyond Convexity, Non-Asymptotic Rate and Acceleration
- ICLR 2023PowerQuant: Automorphism Search for Non-Uniform Quantization
- ICLR 2023Scaffolding a Student to Instill Knowledge
- ICLR 2023Win: Weight-Decay-Integrated Nesterov Acceleration for Adaptive Gradient Algorithms
- ICML 2023Anti-Exploration by Random Network Distillation
- ICML 2023Auxiliary Modality Learning with Generalized Curriculum Distillation
- ICML 2023Effective and Efficient Structural Inference with Reservoir Computing
- ICML 2023Fast Inference from Transformers via Speculative Decoding
- ICML 2023Fast Private Kernel Density Estimation via Locality Sensitive Quantization
- ICML 2023Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks?
- ICML 2023MixFlows: principled variational inference via mixed flows
- NeurIPS 2023Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics
- NeurIPS 2023Conformalized matrix completion
- NeurIPS 2023Continuous-time Analysis of Anchor Acceleration
- NeurIPS 2023Counterfactually Comparing Abstaining Classifiers
- NeurIPS 2023Differentially Private Statistical Inference through $\beta$-Divergence One Posterior Sampling
- NeurIPS 2023Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee
- NeurIPS 2023First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities
- NeurIPS 2023Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration
- NeurIPS 2023Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds
- NeurIPS 2023Knowledge Distillation for High Dimensional Search Index
- NeurIPS 2023Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查推理加速在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "inference-acceleration"}
常见问题
- 2023–2026 年四大会议一共有多少篇推理加速论文？
- 共 259 篇，按年份分别是 2023 年 54 篇、2024 年 50 篇、2025 年 64 篇、2026 年 91 篇。
- NeurIPS 2026 有多少篇推理加速论文？
- NeurIPS 2026 有 33 篇推理加速论文，上一届是 15 篇。
- ICLR 2026 有多少篇推理加速论文？
- ICLR 2026 有 17 篇推理加速论文，上一届是 18 篇。
- ICML 2026 有多少篇推理加速论文？
- ICML 2026 有 26 篇推理加速论文，上一届是 22 篇。
- CVPR 2026 有多少篇推理加速论文？
- CVPR 2026 有 15 篇推理加速论文，上一届是 9 篇。
- 哪个会议的推理加速论文最多？
- NeurIPS，2023–2026 年共 90 篇。