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

241 papers, page 2 of 5

51. NeurIPS 2025Dr. RAW: Towards General High-Level Vision from RAW with Efficient Task Conditioning
52. NeurIPS 2025Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights
53. NeurIPS 2025Dual Prototype-Enhanced Contrastive Framework for Class-Imbalanced Graph Domain Adaptation
54. NeurIPS 2025DUO: No Compromise to Accuracy Degradation
55. NeurIPS 2025Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks
56. NeurIPS 2025ECO: Evolving Core Knowledge for Efficient Transfer
57. NeurIPS 2025Efficient $k$-Sparse Band–Limited Interpolation with Improved Approximation Ratio
58. NeurIPS 2025Efficient Data Selection at Scale via Influence Distillation
59. NeurIPS 2025Efficient Large Language Model Inference with Neural Block Linearization
60. NeurIPS 2025Efficient Last-Iterate Convergence in Solving Extensive-Form Games
61. NeurIPS 2025Efficient Low Rank Attention for Long-Context Inference in Large Language Models
62. NeurIPS 2025Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems
63. NeurIPS 2025Efficient Safe Meta-Reinforcement Learning: Provable Near-Optimality and Anytime Safety
64. NeurIPS 2025Efficient Training of Minimal and Maximal Low-Rank Recurrent Neural Networks
65. NeurIPS 2025EMLoC: Emulator-based Memory-efficient Fine-tuning with LoRA Correction
66. NeurIPS 2025Enhanced Self-Distillation Framework for Efficient Spiking Neural Network Training
67. NeurIPS 2025Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size
68. NeurIPS 2025Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation
69. NeurIPS 2025F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
70. NeurIPS 2025FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic
71. NeurIPS 2025Fantastic Features and Where to Find Them: A Probing Method to combine Features from Multiple Foundation Models
72. NeurIPS 2025Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
73. NeurIPS 2025FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
74. NeurIPS 2025Finding Low-Rank Matrix Weights in DNNs via Riemannian Optimization: RAdaGrad and RAdamW
75. NeurIPS 2025Fira: Can We Achieve Full-rank Training of LLMs Under Low-rank Constraint?
76. NeurIPS 2025FlashBias: Fast Computation of Attention with Bias
77. NeurIPS 2025FlyLoRA: Boosting Task Decoupling and Parameter Efficiency via Implicit Rank-Wise Mixture-of-Experts
78. NeurIPS 2025FocalCodec: Low-Bitrate Speech Coding via Focal Modulation Networks
79. NeurIPS 2025FOCUS: Internal MLLM Representations for Efficient Fine-Grained Visual Question Answering
80. NeurIPS 2025FP4 All the Way: Fully Quantized Training of Large Language Models
81. NeurIPS 2025From Condensation to Rank Collapse: A Two-Stage Analysis of Transformer Training Dynamics
82. NeurIPS 2025Functional Complexity-adaptive Temporal Tensor Decomposition
83. NeurIPS 2025GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation
84. NeurIPS 2025Gated Integration of Low-Rank Adaptation for Continual Learning of Large Language Models
85. NeurIPS 2025GeGS-PCR: Fast and Robust Color 3D Point Cloud Registration with Two-Stage Geometric-3DGS Fusion
86. NeurIPS 2025Generalization Bounds for Rank-sparse Neural Networks
87. NeurIPS 2025GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters
88. NeurIPS 2025Geometry-Aware Collaborative Multi-Solutions Optimizer for Model Fine-Tuning with Parameter Efficiency
89. NeurIPS 2025GoRA: Gradient-driven Adaptive Low Rank Adaptation
90. NeurIPS 2025GraLoRA: Granular Low-Rank Adaptation for Parameter-Efficient Fine-Tuning
91. NeurIPS 2025Graph Data Selection for Domain Adaptation: A Model-Free Approach
92. NeurIPS 2025Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning
93. NeurIPS 2025Hawaii: Hierarchical Visual Knowledge Transfer for Efficient Vision-Language Models
94. NeurIPS 2025HeavyWater and SimplexWater: Distortion-free LLM Watermarks for Low-Entropy Distributions
95. NeurIPS 2025HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts
96. NeurIPS 2025Heterogeneous Diffusion Structure Inference for Network Cascade
97. NeurIPS 2025Hierachical Balance Packing: Towards Efficient Supervised Fine-tuning for Long-Context LLM
98. NeurIPS 2025Hierarchical Optimization via LLM-Guided Objective Evolution for Mobility-on-Demand Systems
99. NeurIPS 2025High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model
100. NeurIPS 2025HiMoLE: Towards OOD-Robust LoRA via Hierarchical Mixture of Experts

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.