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

507 papers, page 4 of 11

151. ICLR 2026Sequences of Logits Reveal the Low Rank Structure of Language Models
152. ICLR 2026SERQ: Saliency-Aware Low-Rank Error Reconstruction for LLM Quantization
153. ICLR 2026SHE-LoRA: Selective Homomorphic Encryption for Federated Tuning with Heterogeneous LoRA
154. ICLR 2026SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse–Linear Attention
155. ICLR 2026SpareTrain: Fault-Tolerant LLM Training via Low-Cost Dual Modular Redundancy
156. ICLR 2026Sparse Attention Adaptation for Long Reasoning
157. ICLR 2026SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting
158. ICLR 2026Stable-LoRA: Stabilizing Feature Learning of Low-Rank Adaption
159. ICLR 2026STaMP: Sequence Transformation and Mixed Precision for Low-Precision Activation Quantization
160. ICLR 2026Study of Training Dynamics for Memory-Constrained Fine-Tuning
161. ICLR 2026SumRA: Parameter Efficient Fine-tuning with Singular Value Decomposition and Summed Orthogonal Basis
162. ICLR 2026Taming Momentum: Rethinking Optimizer States Through Low-Rank Approximation
163. ICLR 2026Task-Adaptive Parameter-Efficient Fine-Tuning for Weather Foundation Models
164. ICLR 2026The Power of Small Initialization in Noisy Low-Tubal-Rank Tensor Recovery
165. ICLR 2026The Rank and Gradient Lost in Non-stationarity: Sample Weight Decay for Mitigating Plasticity Loss in Reinforcement Learning
166. ICLR 2026Three Forward, One Backward: Memory-Efficient Full-Rank Fine-Tuning of Large Models via Extra Forward Passes
167. ICLR 2026Tina: Tiny Reasoning Models via LoRA
168. ICLR 2026TiTok: Transfer Token-level Knowledge via Contrastive Excess to Transplant LoRA
169. ICLR 2026Towards Efficient Optimizer Design for LLM via Structured Fisher Approximation with a Low-Rank Extension
170. ICLR 2026Towards Understanding the Nature of Attention with Low-Rank Sparse Decomposition
171. ICLR 2026TRAC: Tensor-Train based Across-layer Compression for Parameter-Efficient Fine-Tuning
172. ICLR 2026Tractability via Low Dimensionality: The Parameterized Complexity of Training Quantized Neural Networks
173. ICLR 2026ULD-Net: Enabling Ultra-Low-Degree Fully Polynomial Networks for Homomorphically Encrypted Inference
174. ICLR 2026Unbalanced Soft-Matching Distance For Neural Representational Comparison With Partial Unit Correspondence
175. ICLR 2026Understanding Transformers for Time Series: Rank Structure, Flow-of-ranks, and Compressibility
176. ICLR 2026UniQL: Unified Quantization and Low-rank Compression for Adaptive Edge LLMs
177. ICLR 2026Video Unlearning via Low-Rank Refusal Vector
178. ICLR 2026VQ-Transplant: Efficient VQ-Module Integration for Pre-trained Visual Tokenizers
179. ICLR 2026What Layers When: Learning to Skip Compute in LLMs with Residual Gates
180. ICLR 2026When and Where to Reset Matters for Long-Term Test-Time Adaptation
181. ICLR 2026Why High-rank Neural Networks Generalize?: An Algebraic Framework with RKHSs
182. ICLR 2026Why Low-Precision Transformer Training Fails: An Analysis on Flash Attention
183. ICLR 2026WSVD: Weighted Low-Rank Approximation for Fast and Efficient Execution of Low-Precision Vision-Language Models
184. ICLR 2026ZeroSiam: An Efficient Siamese for Test-Time Entropy Optimization without Collapse
185. ICLR 2025$InterLCM$: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration
186. ICLR 2025A Differentiable Rank-Based Objective for Better Feature Learning
187. ICLR 2025A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning
188. ICLR 2025Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
189. ICLR 2025Adaptive Rank Allocation: Speeding Up Modern Transformers with RaNA Adapters
190. ICLR 2025AdaRankGrad: Adaptive Gradient Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning
191. ICLR 2025Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models
192. ICLR 2025ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
193. ICLR 2025An Efficient Framework for Crediting Data Contributors of Diffusion Models
194. ICLR 2025Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation
195. ICLR 2025Binary Losses for Density Ratio Estimation
196. ICLR 2025BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
197. ICLR 2025Black Sheep in the Herd: Playing with Spuriously Correlated Attributes for Vision-Language Recognition
198. ICLR 2025Block-Attention for Efficient Prefilling
199. ICLR 2025Cached Multi-Lora Composition for Multi-Concept Image Generation
200. ICLR 2025Can LLMs Really Learn to Translate a Low-Resource Language from One Grammar Book?

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.