Low-Rank Adaptation papers, 2023–2026

Key findings

• Low-Rank Adaptation went from 282 papers in 2023 to 841 in 2026, roughly 3.0x in three years.
• NeurIPS publishes the most Low-Rank Adaptation work: 781 papers from 2023 to 2026, 34% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 4 in 2023 to 61 in 2026.
• Among the 5 topics under Optimization and Scaling, it ranks #1 by 2026 paper count; the fastest grower in the group, Scaling Laws, is up 4.1x versus 3.0x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026$\delta$-Mem: : Efficient Online Memory For Large Language Models
• ICML 2026A3: an Analytical Low-Rank Approximation Framework for Attention
• ICLR 2026A Guardrail for Safety Preservation: When Safety-Sensitive Subspace Meets Harmful-Resistant Null-Space
• CVPR 20262-Shots in the Dark Low-Light Denoising with Minimal Data Acquisition
• NeurIPS 2025A geometric framework for momentum-based optimizers for low-rank training
• ICML 2025Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning
• ICLR 2025A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning
• CVPR 2025AdaDARE-gamma: Balancing Stability and Plasticity in Multi-modal LLMs through Efficient Adaptation
• NeurIPS 2024Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation
• ICML 2024A Tensor Decomposition Perspective on Second-order RNNs
• ICLR 2024A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
• CVPR 2024DePT: Decoupled Prompt Tuning
• NeurIPS 2023A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression
• ICML 2023A Three-regime Model of Network Pruning
• ICLR 2023A General Rank Preserving Framework for Asymmetric Image Retrieval
• CVPR 20231% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions
• NeurIPS 2026A low-rank decoder bottleneck bounds reliability in foundation-model perturbation prediction
• ICML 2026Adaptive Utilization of Low-Rank Adaptation via Conditioned Gating
• ICLR 2026ABBA-Adapters: Efficient and Expressive Fine-Tuning of Foundation Models
• CVPR 2026Basis-Oriented Low-rank Transfer for Few-Shot and Test-Time Adaptation

All Low-Rank Adaptation papers

507 papers, page 2 of 11

51. ICLR 2026Efficient Spatially-Variant Convolution via Differentiable Sparse Kernel Complex
52. ICLR 2026EffiVMT: Video Motion Transfer via Efficient Spatial-Temporal Decoupled Finetuning
53. ICLR 2026Enabling Fine-Tuning of Direct Feedback Alignment via Feedback-Weight Matching
54. ICLR 2026Escaping Low-Rank Traps: Interpretable Visual Concept Learning via Implicit Vector Quantization
55. ICLR 2026Exposing Mixture and Annotating Confusion for Active Universal Test-Time Adaptation
56. ICLR 2026Faster Parameter-Free Regret Matching Algorithms
57. ICLR 2026FFT-based Dynamic Subspace Selection for Low-Rank Adaptive Optimization of Large Language Models
58. ICLR 2026Fine-tuning Quantized Neural Networks with Zeroth-order Optimization
59. ICLR 2026Flatness Guided Test-Time Adaptation for Vision-Language Models
60. ICLR 2026FlexiCodec: A Dynamic Neural Audio Codec for Low Frame Rates
61. ICLR 2026FlexLoRA: Entropy-Guided Flexible Low-Rank Adaptation
62. ICLR 2026FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment
63. ICLR 2026Fluent Alignment with Disfluent Judges: Post-training for lower-resource languages
64. ICLR 2026Fly-CL: A Fly-Inspired Framework for Enhancing Efficient Decorrelation and Reduced Training Time in Pre-trained Model-based Continual Representation Learning
65. ICLR 2026Frozen Priors, Fluid Forecasts: Prequential Uncertainty for Low-Data Deployment with Pretrained Generative Models
66. ICLR 2026FS-KAN: Permutation Equivariant Kolmogorov-Arnold Networks via Function Sharing
67. ICLR 2026GLASS Flows: Efficient Inference for Reward Alignment of Flow and Diffusion Models
68. ICLR 2026GlowQ: Group-Shared LOw-Rank Approximation for Quantized LLMs
69. ICLR 2026Gradient Descent Dynamics of Rank-One Matrix Denoising
70. ICLR 2026Gradient Intrinsic Dimensionality Alignment：Narrowing The Gap Between Low-Rank Adaptation and Full Fine-Tuning
71. ICLR 2026GradPruner: Gradient-guided Layer Pruning Enabling Efficient Fine-Tuning and Inference for LLMs
72. ICLR 2026HEAPr: Hessian-based Efficient Atomic Expert Pruning in Output Space
73. ICLR 2026Heterogeneous Federated Fine-Tuning with Parallel One-Rank Adaptation
74. ICLR 2026Hidden Breakthroughs in Language Model Training
75. ICLR 2026HippoTune: A Hippocampal Associative Loop–Inspired Fine-Tuning Method for Continual Learning
76. ICLR 2026Homeostatic Adaptation of Optimal Population Codes under Metabolic Stress
77. ICLR 2026Hystar: Hypernetwork-driven Style-adaptive Retrieval via Dynamic SVD Modulation
78. ICLR 2026IA2: Alignment with ICL Activations improves Supervised Fine-Tuning
79. ICLR 2026IDEAL: Data Equilibrium Adaptation for Multi-Capability Language Model Alignment
80. ICLR 2026IGU-LoRA: Adaptive Rank Allocation via Integrated Gradients and Uncertainty-Aware Scoring
81. ICLR 2026Implicit Bias and Loss of Plasticity in Matrix Completion: Depth Promotes Low-Rankness
82. ICLR 2026IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation
83. ICLR 2026INSTANT: Compressing Gradients and Activations for Resource-Efficient Training
84. ICLR 2026Intrinsic training dynamics of deep neural networks
85. ICLR 2026Is Finer Better? The Limits of Microscaling Formats in Large Language Models
86. ICLR 2026JailbreakLoRA: Your Downloaded LoRA from Sharing Platforms might be Unsafe
87. ICLR 2026KeepLoRA: Continual Learning with Residual Gradient Adaptation
88. ICLR 2026LaplacianFormer:Rethinking Linear Attention with Laplacian Kernel
89. ICLR 2026Large Language Model Compression with Global Rank and Sparsity Optimization
90. ICLR 2026Learning Structure-Semantic Evolution Trajectories for Graph Domain Adaptation
91. ICLR 2026Learning to Interpret Weight Differences in Language Models
92. ICLR 2026LoFT: Low-Rank Adaptation That Behaves Like Full Fine-Tuning
93. ICLR 2026LogART: Pushing the Limit of Efficient Logarithmic Post-Training Quantization
94. ICLR 2026LoRA meets Riemannion: Muon Optimizer for Parametrization-independent Low-Rank Adapters
95. ICLR 2026LoRA-Mixer: Coordinate Modular LoRA Experts Through Serial Attention Routing
96. ICLR 2026LoRA-S: An Efficient Low Rank Adaptation scheme via Sylvester equation
97. ICLR 2026LoRAGen: Structure-Aware Weight Space Learning for LoRA Generation
98. ICLR 2026Low rank adaptation of chemical foundation models generate effective odorant representations
99. ICLR 2026Low Rank Transformer for Multivariate Time Series Anomaly Detection and Localization
100. ICLR 2026Low-pass Personalized Subgraph Federated Recommendation

FAQ

How many Low-Rank Adaptation papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,273 in total: 282 in 2023, 518 in 2024, 632 in 2025, 841 in 2026.

How many Low-Rank Adaptation papers are at NeurIPS 2026?

NeurIPS 2026 has 269 Low-Rank Adaptation papers, versus 241 the year before.

How many Low-Rank Adaptation papers are at ICLR 2026?

ICLR 2026 has 184 Low-Rank Adaptation papers, versus 152 the year before.

How many Low-Rank Adaptation papers are at ICML 2026?

ICML 2026 has 240 Low-Rank Adaptation papers, versus 136 the year before.

How many Low-Rank Adaptation papers are at CVPR 2026?

CVPR 2026 has 148 Low-Rank Adaptation papers, versus 103 the year before.

Which conference publishes the most Low-Rank Adaptation papers?

NeurIPS, with 781 papers from 2023 to 2026.