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

632 papers, page 4 of 13

151. ICLR 2025Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models
152. ICLR 2025Federated Residual Low-Rank Adaptation of Large Language Models
153. ICLR 2025Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment
154. ICLR 2025Find A Winning Sign: Sign Is All We Need to Win the Lottery
155. ICLR 2025Fine-tuning with Reserved Majority for Noise Reduction
156. ICLR 2025Fitting Networks with a Cancellation Trick
157. ICLR 2025Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
158. ICLR 2025GeoLoRA: Geometric integration for parameter efficient fine-tuning
159. ICLR 2025GraphBridge: Towards Arbitrary Transfer Learning in GNNs
160. ICLR 2025HeadMap: Locating and Enhancing Knowledge Circuits in LLMs
161. ICLR 2025HiRA: Parameter-Efficient Hadamard High-Rank Adaptation for Large Language Models
162. ICLR 2025HMoRA: Making LLMs More Effective with Hierarchical Mixture of LoRA Experts
163. ICLR 2025How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings
164. ICLR 2025How Low Can You Go? Searching for the Intrinsic Dimensionality of Complex Networks using Metric Node Embeddings
165. ICLR 2025KaSA: Knowledge-Aware Singular-Value Adaptation of Large Language Models
166. ICLR 2025Lambda-Skip Connections: the architectural component that prevents Rank Collapse
167. ICLR 2025Large Convolutional Model Tuning via Filter Subspace
168. ICLR 2025LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics
169. ICLR 2025Learning-Augmented Frequent Directions
170. ICLR 2025LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
171. ICLR 2025LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning
172. ICLR 2025LoLCATs: On Low-Rank Linearizing of Large Language Models
173. ICLR 2025Long-Context Linear System Identification
174. ICLR 2025LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation
175. ICLR 2025LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
176. ICLR 2025LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
177. ICLR 2025LoRA-X: Bridging Foundation Models with Training-Free Cross-Model Adaptation
178. ICLR 2025LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation models
179. ICLR 2025LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning
180. ICLR 2025Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning
181. ICLR 2025MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba
182. ICLR 2025Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
183. ICLR 2025MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projection
184. ICLR 2025MCNC: Manifold-Constrained Reparameterization for Neural Compression
185. ICLR 2025Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering
186. ICLR 2025MeteoRA: Multiple-tasks Embedded LoRA for Large Language Models
187. ICLR 2025MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling
188. ICLR 2025MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture of Shards
189. ICLR 2025MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion
190. ICLR 2025MTSAM: Multi-Task Fine-Tuning for Segment Anything Model
191. ICLR 2025NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance
192. ICLR 2025Noisy Test-Time Adaptation in Vision-Language Models
193. ICLR 2025OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition
194. ICLR 2025On Large Language Model Continual Unlearning
195. ICLR 2025On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning
196. ICLR 2025On the Benefits of Attribute-Driven Graph Domain Adaptation
197. ICLR 2025On the Crucial Role of Initialization for Matrix Factorization
198. ICLR 2025On the Optimization Landscape of Low Rank Adaptation Methods for Large Language Models
199. ICLR 2025PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
200. ICLR 2025Palu: KV-Cache Compression with Low-Rank Projection

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.