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

193 papers, page 2 of 4

51. NeurIPS 2024Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection
52. NeurIPS 2024Entrywise error bounds for low-rank approximations of kernel matrices
53. NeurIPS 2024Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems
54. NeurIPS 2024Expanding Sparse Tuning for Low Memory Usage
55. NeurIPS 2024Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing
56. NeurIPS 2024F-OAL: Forward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning
57. NeurIPS 2024Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers
58. NeurIPS 2024Federated Black-Box Adaptation for Semantic Segmentation
59. NeurIPS 2024Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources
60. NeurIPS 2024Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond
61. NeurIPS 2024Fit for our purpose, not yours: Benchmark for a low-resource, Indigenous language
62. NeurIPS 2024FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
63. NeurIPS 2024FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
64. NeurIPS 2024FouRA: Fourier Low-Rank Adaptation
65. NeurIPS 2024From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement
66. NeurIPS 2024Frustratingly Easy Test-Time Adaptation of Vision-Language Models
67. NeurIPS 2024Geometry-aware training of factorized layers in tensor Tucker format
68. NeurIPS 2024Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing
69. NeurIPS 2024Group and Shuffle: Efficient Structured Orthogonal Parametrization
70. NeurIPS 2024Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
71. NeurIPS 2024Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models
72. NeurIPS 2024How do Large Language Models Handle Multilingualism?
73. NeurIPS 2024HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning
74. NeurIPS 2024Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis
75. NeurIPS 2024Improving Deep Learning Optimization through Constrained Parameter Regularization
76. NeurIPS 2024Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation
77. NeurIPS 2024Indoor Air Quality Dataset with Activities of Daily Living in Low to Middle-income Communities
78. NeurIPS 2024Inferring stochastic low-rank recurrent neural networks from neural data
79. NeurIPS 2024Instruction Tuning With Loss Over Instructions
80. NeurIPS 2024IODA: Instance-Guided One-shot Domain Adaptation for Super-Resolution
81. NeurIPS 2024Is Multiple Object Tracking a Matter of Specialization?
82. NeurIPS 2024Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
83. NeurIPS 2024KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization
84. NeurIPS 2024L-TTA: Lightweight Test-Time Adaptation Using a Versatile Stem Layer
85. NeurIPS 2024LaSCal: Label-Shift Calibration without target labels
86. NeurIPS 2024Learn more, but bother less: parameter efficient continual learning
87. NeurIPS 2024Learning De-Biased Representations for Remote-Sensing Imagery
88. NeurIPS 2024Learning Discrete Latent Variable Structures with Tensor Rank Conditions
89. NeurIPS 2024Learning Elastic Costs to Shape Monge Displacements
90. NeurIPS 2024Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks
91. NeurIPS 2024Learning from Offline Foundation Features with Tensor Augmentations
92. NeurIPS 2024Learning Low-Rank Feature for Thorax Disease Classification
93. NeurIPS 2024Leveraging partial stragglers within gradient coding
94. NeurIPS 2024LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low Resource and Extinct Languages
95. NeurIPS 2024LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
96. NeurIPS 2024LoFiT: Localized Fine-tuning on LLM Representations
97. NeurIPS 2024Loki: Low-rank Keys for Efficient Sparse Attention
98. NeurIPS 2024Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation
99. NeurIPS 2024LoQT: Low-Rank Adapters for Quantized Pretraining
100. NeurIPS 2024LoRA-GA: Low-Rank Adaptation with Gradient Approximation

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.