Sparsity Acceleration papers, 2023–2026

Key findings

• Sparsity Acceleration went from 54 papers in 2023 to 89 in 2026, roughly 1.6x in three years.
• NeurIPS publishes the most Sparsity Acceleration work: 80 papers from 2023 to 2026, 31% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 0 in 2023 to 13 in 2026.
• Among the 5 topics under Hardware and Compilers, it ranks #1 by 2026 paper count; the fastest grower in the group, Edge Inference, is up 4.0x versus 1.6x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026AC/DC on a Budget -- Alternating Sparse Phases
• ICML 2026An Evidential Route to Asymptotic Bayes Optimality under Sparsity
• ICLR 2026Hilbert-Guided Sparse Local Attention
• CVPR 2026Improving Sparse Autoencoder with Dynamic Attention
• NeurIPS 2025Bilevel Network Learning via Hierarchically Structured Sparsity
• ICML 2025COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning
• ICLR 2025Beyond Worst-Case Dimensionality Reduction for Sparse Vectors
• CVPR 2025ICP: Immediate Compensation Pruning for Mid-to-high Sparsity
• NeurIPS 2024ELSA: Exploiting Layer-wise N:M Sparsity for Vision Transformer Acceleration
• ICML 2024Accelerating Transformer Pre-training with 2:4 Sparsity
• ICLR 2024Adaptive Sharpness-Aware Pruning for Robust Sparse Networks
• CVPR 2024Masked Spatial Propagation Network for Sparsity-Adaptive Depth Refinement
• NeurIPS 2023Dynamic Sparsity Is Channel-Level Sparsity Learner
• ICML 2023Conformalization of Sparse Generalized Linear Models
• ICLR 2023Bit-Pruning: A Sparse Multiplication-Less Dot-Product
• CVPR 2023Adaptive Channel Sparsity for Federated Learning Under System Heterogeneity
• NeurIPS 2026Beyond Masked Sparsity: SNACK Enables Truly Sparse Neural Networks on GPU
• ICML 2026FlashSketch: Sketch-Kernel Co-Design for Fast Sparse Sketching on GPUs
• ICLR 2026Identifiability Challenges in Sparse Linear Ordinary Differential Equations
• CVPR 2026Revisiting Pose Sensitivity in Splat-based Computed Tomography under Sparse-view Reconstruction

All Sparsity Acceleration papers

260 papers, page 2 of 6

51. ICML 2026Narrowing the ANN–SNN Gap for Continuous 1D Temporal Signal Classification with Multi-Scale Temporal Encoding and Sparsity-Regularized Transform Encoding
52. ICML 2026Prism: Spectral-Aware Block-Sparse Attention
53. ICML 2026RSTR: Reducing SpatioTemporal Redundancy in Diffusion Transformers
54. ICML 2026RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models
55. ICML 2026Size Transferability of Graph Convolutional Networks across Sparsity: A Generalized Graphon Perspective
56. ICML 2026SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity
57. ICML 2026SparseOpt: Addressing Normalization-induced Gradient Skew in Sparse Training
58. ICML 2026Sparser Block-Sparse Attention via Token Permutation
59. ICML 2026Weight-sparse transformers have interpretable circuits
60. ICML 2026When Does Sparsity Mitigate the Curse of Depth in LLMs
61. NeurIPS 2026AC/DC on a Budget -- Alternating Sparse Phases
62. NeurIPS 2026Asymmetric Scaling Laws from Sparse Features
63. NeurIPS 2026Attribute-Efficient Learning of Sparse Halfspaces with Constant Malicious Noise Rate
64. NeurIPS 2026Beyond Masked Sparsity: SNACK Enables Truly Sparse Neural Networks on GPU
65. NeurIPS 2026Cannistraci-Hebb Channel-wise Dynamic Sparse Training of Convolutional Neural Networks with Contextual Modulation
66. NeurIPS 2026Coarse-to-Fine 3D MRI Reconstruction via Resolution-Agnostic Neural Operators
67. NeurIPS 2026Colour me shocked: Exact Molecular Hessians from MLIPs in O(N) time using sparse differentiation!
68. NeurIPS 2026Contribution-Aware Structured Sparsity for Model Merging
69. NeurIPS 2026Direct Acceleration of Stochastic Root-Finding Without Variance Reduction and Regularization
70. NeurIPS 2026Distribution Free Fourier Sparsity Testing
71. NeurIPS 2026Effectiveness of Curriculum Learning Depends on Reward Sparsity and Competing Optima
72. NeurIPS 2026Efficient Fine-Tuning for Structured Sparsity Under Group Repartitioning
73. NeurIPS 2026Flow Matching from Viewpoint of Proximal Operators
74. NeurIPS 2026Inference-time Alignment via Sparse Junction Steering
75. NeurIPS 2026Intrinsically Interpretable Attention via Sparse Post-Training
76. NeurIPS 2026Inverting Retargeting: Humanoid Datasets Remember Their Operators
77. NeurIPS 2026Learning Event-to-Field Operators Without Interpolation
78. NeurIPS 2026Long-Context Language Models Require Extreme Sparsity in Context Dimension
79. NeurIPS 2026On the Sparsity of Direct Preference Optimization: Weight Disentanglement in the NTK Regime
80. NeurIPS 2026On the Sparsity-Storage-Accuracy Tradeoff in Parsimoniously Activated Dictionary Learning
81. NeurIPS 2026OneVision-Encoder: Codec-Aligned Sparsity as a Foundational Principle for Multimodal Intelligence
82. NeurIPS 2026Perfect Parallelization in Mini-Batch SGD with Classical Momentum Acceleration
83. NeurIPS 2026Posterior Contraction Rates for sparse Kolmogorov-Arnold Networks in Anisotropic Besov Spaces
84. NeurIPS 2026Sparse blind deconvolution via thresholded Wirtinger flow
85. NeurIPS 2026Sparse Delta Memory: Scaling the State of Linear RNNs through Sparsity
86. NeurIPS 2026Sparse Sum-of-Squares Layers for Certified Learning
87. NeurIPS 2026SVDP: Training-Free Contextual Sparsity Predictors for Fast LLM Inference
88. NeurIPS 2026The Sparsity Whisperer
89. NeurIPS 2026Transferable SCF-Acceleration through Solver-Aligned Initialization Learning
90. CVPR 2025CASP: Compression of Large Multimodal Models Based on Attention Sparsity
91. CVPR 2025ICP: Immediate Compensation Pruning for Mid-to-high Sparsity
92. CVPR 2025MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds
93. CVPR 2025S2Gaussian: Sparse-View Super-Resolution 3D Gaussian Splatting
94. CVPR 2025SINR: Sparsity Driven Compressed Implicit Neural Representations
95. ICLR 2025Beyond Worst-Case Dimensionality Reduction for Sparse Vectors
96. ICLR 2025Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
97. ICLR 2025DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle
98. ICLR 2025Dynamic Low-Rank Sparse Adaptation for Large Language Models
99. ICLR 2025Efficient Sparse PCA via Block-Diagonalization
100. ICLR 2025From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency

FAQ

How many Sparsity Acceleration papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

260 in total: 54 in 2023, 53 in 2024, 64 in 2025, 89 in 2026.

How many Sparsity Acceleration papers are at NeurIPS 2026?

NeurIPS 2026 has 29 Sparsity Acceleration papers, versus 21 the year before.

How many Sparsity Acceleration papers are at ICLR 2026?

ICLR 2026 has 24 Sparsity Acceleration papers, versus 16 the year before.

How many Sparsity Acceleration papers are at ICML 2026?

ICML 2026 has 24 Sparsity Acceleration papers, versus 22 the year before.

How many Sparsity Acceleration papers are at CVPR 2026?

CVPR 2026 has 12 Sparsity Acceleration papers, versus 5 the year before.

Which conference publishes the most Sparsity Acceleration papers?

NeurIPS, with 80 papers from 2023 to 2026.