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

840 papers, page 4 of 17

151. ICLR 2026ABBA-Adapters: Efficient and Expressive Fine-Tuning of Foundation Models
152. ICLR 2026Achieving low-bit Muon through subspace preservation and grid quantization
153. ICLR 2026Actions as Language: Fine-Tuning VLMs into VLAs Without Catastrophic Forgetting
154. ICLR 2026Adaptive Debiasing Tsallis Entropy for Test-Time Adaptation
155. ICLR 2026Adaptive Nonlinear Compression for Large Foundation Models
156. ICLR 2026AdaRank: Adaptive Rank Pruning for Enhanced Model Merging
157. ICLR 2026ADEPT: Continual Pretraining via Adaptive Expansion and Dynamic Decoupled Tuning
158. ICLR 2026Alignment-Enhanced Integration of Connectivity and Spectral Sparse in Dynamic Sparse Training of LLM
159. ICLR 2026All-day Multi-scenes Lifelong Vision-and-Language Navigation with Tucker Adaptation
160. ICLR 2026Arbitrary-Order Block SignSGD for Memory-Efficient LLM Fine-Tuning
161. ICLR 2026Are we measuring oversmoothing in graph neural networks correctly?
162. ICLR 2026Auditing Black-Box LLM APIs with a Rank-Based Uniformity Test
163. ICLR 2026Autoregressive-based Progressive Coding for Ultra-Low Bitrate Image Compression
164. ICLR 2026BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models
165. ICLR 2026Bayesian Evidence-Driven Prototype Evolution for Federated Domain Adaptation
166. ICLR 2026Bayesian Test-Time Adaptation via Dirichlet feature projection and GMM-Driven Inference for Motor Imagery EEG Decoding
167. ICLR 2026Bi-LoRA: Efficient Sharpness-Aware Minimization for Fine-Tuning Large-Scale Models
168. ICLR 2026Bilateral Information-aware Test-time Adaptation for Vision-Language Models
169. ICLR 2026BoRA: Towards More Expressive Low-Rank Adaptation with Block Diversity
170. ICLR 2026Breaking Scale Anchoring: Frequency Representation Learning for Accurate High-Resolution Inference from Low-Resolution Training
171. ICLR 2026Bridging Radiology and Pathology Foundation Models via Concept-Based Multimodal Co-Adaptation
172. ICLR 2026CAR-LoRA: Training Compression-Aware and Robust LoRA Adapters for Evolving LLMs
173. ICLR 2026CARE: Covariance-Aware and Rank-Enhanced Decomposition for Enabling Multi-Head Latent Attention
174. ICLR 2026CGSA: Class-Guided Slot-Aware Adaptation for Source-Free Object Detections
175. ICLR 2026ChainGPT: Dual-Reasoning Model with Recurrent Depth and Multi-Rank State Updates
176. ICLR 2026Characteristic Root Analysis and Regularization for Linear Time Series Forecasting
177. ICLR 2026CodeQuant: Unified Clustering and Quantization for Enhanced Outlier Smoothing in Low-Precision Mixture-of-Experts
178. ICLR 2026Consistent Low-Rank Approximation
179. ICLR 2026Continual Low-Rank Adapters for LLM-based Generative Recommender Systems
180. ICLR 2026Controllable First-Frame-Guided Video Editing via Mask-Aware LoRA Fine-Tuning
181. ICLR 2026CPQS-Tuning: A Model Self-Perception-Based Data Filtering Algorithm for Efficient Instruction Fine-Tuning
182. ICLR 2026CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure
183. ICLR 2026DADA: Dual Averaging with Distance Adaptation
184. ICLR 2026Deep Hierarchical Learning with Nested Subspace Networks
185. ICLR 2026Deep Learning with Learnable Product-Structured Activations
186. ICLR 2026Designing Rules to Pick a Rule: Aggregation by Consistency
187. ICLR 2026Developmental Federated Tuning: A Cognitive-Inspired Paradigm for Efficient LLM Adaptation
188. ICLR 2026DiaBlo: Diagonal Blocks Are Sufficient For Finetuning
189. ICLR 2026Distributionally Robust Classification for Multi-source Unsupervised Domain Adaptation
190. ICLR 2026Do Not Let Low-Probability Tokens Over-Dominate in RL for LLMs
191. ICLR 2026Do We Really Need Permutations? Impact of Width Expansion on Linear Mode Connectivity
192. ICLR 2026Does the Data Processing Inequality Reflect Practice? On the Utility of Low-Level Tasks
193. ICLR 2026DSSA: Dense-Sparse Switchable Attention for Seamless Short-to-Long Adaptation
194. ICLR 2026E²LoRA: Efficient and Effective Low-Rank Adaptation with Entropy-Guided Adaptive Sharing
195. ICLR 2026Efficient Learning on Large Graphs using a Densifying Regularity Lemma
196. ICLR 2026Efficient Orthogonal Fine-Tuning with Principal Subspace Adaptation
197. ICLR 2026Efficient Resource-Constrained Training of Transformers via Subspace Optimization
198. ICLR 2026Efficient Spatially-Variant Convolution via Differentiable Sparse Kernel Complex
199. ICLR 2026EffiVMT: Video Motion Transfer via Efficient Spatial-Temporal Decoupled Finetuning
200. ICLR 2026Enabling Fine-Tuning of Direct Feedback Alignment via Feedback-Weight Matching

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.