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 48 篇,第 1 / 1 页
- ICLR 2026BBQ: Boosting Quantization Entropy with Bell Box Quantization
- ICLR 2026Corner Gradient Descent
- ICLR 2026Dataset Distillation as Pushforward Optimal Quantization
- ICLR 2026DiCache: Let Diffusion Model Determine Its Own Cache
- ICLR 2026Diffusion LLMs Can Do Faster-Than-AR Inference via Discrete Diffusion Forcing
- ICLR 2026Distributionally Robust Linear Regression with Block Lewis Weights
- ICLR 2026Egalitarian Gradient Descent: A Simple Approach to Accelerated Grokking
- ICLR 2026Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding
- ICLR 2026GAS: Improving Discretization of Diffusion ODEs via Generalized Adversarial Solver
- ICLR 2026NLI : Non-uniform Linear Interpolation Approximation of Nonlinear Operations for Efficient LLMs Inference
- ICLR 2026OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework
- ICLR 2026RAPID$^3$: Tri-Level Reinforced Acceleration Policies for Diffusion Transformer
- ICLR 2026Score Distillation Beyond Acceleration: Generative Modeling from Corrupted Data
- ICLR 2026SGD with Adaptive Preconditioning: Unified Analysis and Momentum Acceleration
- ICLR 2026Towards a Universally Transferable Acceleration Method for Density Functional Theory
- ICLR 2026TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate
- ICLR 2026Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)
- ICLR 2025Effective Interplay between Sparsity and Quantization: From Theory to Practice
- ICLR 2025Elucidating the Preconditioning in Consistency Distillation
- ICLR 2025Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity
- ICLR 2025Model Equality Testing: Which Model is this API Serving?
- ICLR 2025Nesterov acceleration in benignly non-convex landscapes
- ICLR 2025One Step Diffusion via Shortcut Models
- ICLR 2025Optimizing $(L_0, L_1)$-Smooth Functions by Gradient Methods
- ICLR 2025PALMBENCH: A COMPREHENSIVE BENCHMARK OF COMPRESSED LARGE LANGUAGE MODELS ON MOBILE PLATFORMS
- ICLR 2025PEARL: Parallel Speculative Decoding with Adaptive Draft Length
- ICLR 2025PFDiff: Training-Free Acceleration of Diffusion Models Combining Past and Future Scores
- ICLR 2025Progressive distillation induces an implicit curriculum
- ICLR 2025Quamba: A Post-Training Quantization Recipe for Selective State Space Models
- ICLR 2025Restructuring Vector Quantization with the Rotation Trick
- ICLR 2025RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs
- ICLR 2025SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration
- ICLR 2025Scaling FP8 training to trillion-token LLMs
- ICLR 2025SGD with memory: fundamental properties and stochastic acceleration
- ICLR 2025SVDQuant: Absorbing Outliers by Low-Rank Component for 4-Bit Diffusion Models
- ICLR 2024Embarrassingly Simple Dataset Distillation
- ICLR 2024InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning
- 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
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。