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

240 papers, page 4 of 5

151. ICML 2026Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates
152. ICML 2026Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
153. ICML 2026PRISM: Gauge-Invariant Tangent-Space Differentially Private LoRA
154. ICML 2026Private and Stable Test-time Adaptation with Differential Privacy
155. ICML 2026Probability-Entropy Calibration: An Elastic Indicator for Adaptive Fine-tuning
156. ICML 2026Progressive Graph Structure Adjustment for Homophily Shift Adaptation
157. ICML 2026ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression
158. ICML 2026Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function
159. ICML 2026Quantifying the Uncertainty of Foundation Models with Singular Value Ensembles
160. ICML 2026RaBiT: Residual Aware Binarization Training for Accurate and Efficient LLMs
161. ICML 2026Rank-Aware Spectral Bounds on Attention Logits for Stable Low-Precision Training
162. ICML 2026Rank-Learner: Orthogonal Ranking of Treatment Effects
163. ICML 2026Rational Neural Networks have Expressivity Advantages
164. ICML 2026Reference-Free Meta-Learning for Generalized Implicit Neural Representation in Efficient MRI Reconstruction
165. ICML 2026Refining Dual Spectral Sparsity in Transformed Tensor Singular Values
166. ICML 2026Representation Drift Compensation: A Near-Zero Inference Cost Enhancement for LLM Decomposition
167. ICML 2026Rethinking Low-Confidence Pseudo Labels: Influence-Aware Semi-Supervised Fine-Tuning for Hyperspectral Change Detection
168. ICML 2026Rethinking Parameter Sharing as Graph Coloring for Structured Compression
169. ICML 2026Rethinking the Flow-based Gradual Domain Adaptation: A Semi-Dual Optimal Transport Perspective
170. ICML 2026Revisiting the Bertrand Paradox via Equilibrium Analysis of No-regret Learners
171. ICML 2026Rewiring Experts on the Fly: Continuous Rerouting for Better Online Adaptation in Mixture-of-Expert Models
172. ICML 2026Riemannian Networks over Full-Rank Correlation Matrices
173. ICML 2026Robust Vision-Language Models via Manifold-Adversarial Adapters
174. ICML 2026SABER: Continual Learning with Representation Conflict Management
175. ICML 2026SALAAD: Sparse And Low-Rank Adaptation via ADMM for Large Language Model Inference
176. ICML 2026SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling
177. ICML 2026Scalable Kronecker-Factored Fisher Approximation for Neural Network Parameter Sensitivity
178. ICML 2026Scaling Inference-Time Computation via Opponent Simulation: Enabling Online Strategic Adaptation in Repeated Negotiation
179. ICML 2026ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
180. ICML 2026SCNS: Continual Personalization of Diffusion Models via Submodular Concept Neuron Selection
181. ICML 2026Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation
182. ICML 2026SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass
183. ICML 2026Simple yet Effective: Low-Rank Spatial Attention for Neural Operators
184. ICML 2026Singular Bayesian Neural Networks
185. ICML 2026SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
186. ICML 2026Sketch-Based Low-Rank Model Merging with Shared Circulant Transforms
187. ICML 2026Skill Neologisms: Towards Skill-based Continual Learning
188. ICML 2026Spectral Bridge Variational Inference: Dynamic LoRA via Bures-Wasserstein Gradient Flows
189. ICML 2026Spectral Imbalance Causes Forgetting in Low-Rank Continual Adaptation
190. ICML 2026SPR-RAFT: Parameter-Efficient Regression-Aware Fine-Tuning for Biomedical LLM Regression
191. ICML 2026SPR: A Structured Prompt Refinement Network for Modality Missing
192. ICML 2026SS-TPT: Stability and Suitability-Guided Test-Time Prompt Tuning for Adversarially Robust Vision-Language Models
193. ICML 2026SSR-Merge: Subspace Signal Routing for Training-Free LoRA Merging in Diffusion Models
194. ICML 2026Stabilizing Native Low-Rank LLM Pretraining
195. ICML 2026STAR-KV: Low-Rank KV Cache Compression via Soft Thresholding for Adaptive Rank Control
196. ICML 2026Stochastic Order Learning: An Approach to Rank Estimation Using Noisy Data
197. ICML 2026Stochastic Sparse Attention for Memory-Bound Inference
198. ICML 2026SubspacePath Pruner: Inference-time Pruning via Probe-based Representation–Parameter Coupling
199. ICML 2026SURGE: Surrogate Gradient Adaptation in Binary Neural Networks
200. ICML 2026Swift-SVD: Theoretical Optimality Meets Practical Efficiency in Low-Rank LLM Compression

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.