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

282 papers, page 5 of 6

201. ICML 2023Uncovering Adversarial Risks of Test-Time Adaptation
202. ICML 2023Using Perturbation to Improve Goodness-of-Fit Tests based on Kernelized Stein Discrepancy
203. ICML 2023What Can Be Learnt With Wide Convolutional Neural Networks?
204. ICML 2023Which Tricks are Important for Learning to Rank?
205. NeurIPS 2023(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
206. NeurIPS 2023A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression
207. NeurIPS 2023A Unified Framework for Rank-based Loss Minimization
208. NeurIPS 2023Adaptive whitening with fast gain modulation and slow synaptic plasticity
209. NeurIPS 2023Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces
210. NeurIPS 2023Algorithmic Regularization in Tensor Optimization: Towards a Lifted Approach in Matrix Sensing
211. NeurIPS 2023Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization
212. NeurIPS 2023Bayesian Extensive-Rank Matrix Factorization with Rotational Invariant Priors
213. NeurIPS 2023Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization
214. NeurIPS 2023Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models
215. NeurIPS 2023Combinatorial Optimization with Policy Adaptation using Latent Space Search
216. NeurIPS 2023Composing Parameter-Efficient Modules with Arithmetic Operation
217. NeurIPS 2023Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes
218. NeurIPS 2023Context-lumpable stochastic bandits
219. NeurIPS 2023Cross-Domain Policy Adaptation via Value-Guided Data Filtering
220. NeurIPS 2023DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation
221. NeurIPS 2023Data Selection for Language Models via Importance Resampling
222. NeurIPS 2023Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence
223. NeurIPS 2023DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
224. NeurIPS 2023Efficient Adaptation of Large Vision Transformer via Adapter Re-Composing
225. NeurIPS 2023Efficient Hyper-parameter Optimization with Cubic Regularization
226. NeurIPS 2023Efficient Low-rank Backpropagation for Vision Transformer Adaptation
227. NeurIPS 2023Efficient Model-Free Exploration in Low-Rank MDPs
228. NeurIPS 2023Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction
229. NeurIPS 2023Efficient Testable Learning of Halfspaces with Adversarial Label Noise
230. NeurIPS 2023Errors-in-variables Fr\'echet Regression with Low-rank Covariate Approximation
231. NeurIPS 2023Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms
232. NeurIPS 2023Fast Rank-1 Lattice Targeted Sampling for Black-box Optimization
233. NeurIPS 2023Feature Adaptation for Sparse Linear Regression
234. NeurIPS 2023Geometric Analysis of Matrix Sensing over Graphs
235. NeurIPS 2023Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces
236. NeurIPS 2023Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products
237. NeurIPS 2023Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
238. NeurIPS 2023Kissing to Find a Match: Efficient Low-Rank Permutation Representation
239. NeurIPS 2023Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback
240. NeurIPS 2023Learning List-Level Domain-Invariant Representations for Ranking
241. NeurIPS 2023Low Tensor Rank Learning of Neural Dynamics
242. NeurIPS 2023Lower Bounds on Adaptive Sensing for Matrix Recovery
243. NeurIPS 2023Matrix Compression via Randomized Low Rank and Low Precision Factorization
244. NeurIPS 2023Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models
245. NeurIPS 2023MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates
246. NeurIPS 2023Multi-Head Adapter Routing for Cross-Task Generalization
247. NeurIPS 2023Neural Priming for Sample-Efficient Adaptation
248. NeurIPS 2023Non-Stationary Bandits with Auto-Regressive Temporal Dependency
249. NeurIPS 2023On the spectral bias of two-layer linear networks
250. NeurIPS 2023Parameter-efficient Tuning of Large-scale Multimodal Foundation Model

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.