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

2,272 papers, page 44 of 46

2151. ICML 2023Hierarchical Imitation Learning with Vector Quantized Models
2152. ICML 2023Human-Timescale Adaptation in an Open-Ended Task Space
2153. ICML 2023HyperTuning: Toward Adapting Large Language Models without Back-propagation
2154. ICML 2023Improved Algorithms for White-Box Adversarial Streams
2155. ICML 2023In Search for a Generalizable Method for Source Free Domain Adaptation
2156. ICML 2023Last Switch Dependent Bandits with Monotone Payoff Functions
2157. ICML 2023Learning in POMDPs is Sample-Efficient with Hindsight Observability
2158. ICML 2023Learning-Rate-Free Learning by D-Adaptation
2159. ICML 2023LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation
2160. ICML 2023Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single
2161. ICML 2023Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning
2162. ICML 2023Mechanistic Mode Connectivity
2163. ICML 2023Multi-User Reinforcement Learning with Low Rank Rewards
2164. ICML 2023Naive imputation implicitly regularizes high-dimensional linear models
2165. ICML 2023NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning
2166. ICML 2023Offline Meta Reinforcement Learning with In-Distribution Online Adaptation
2167. ICML 2023On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation
2168. ICML 2023On Pitfalls of Test-Time Adaptation
2169. ICML 2023On the Role of Attention in Prompt-tuning
2170. ICML 2023One-sided Matrix Completion from Two Observations Per Row
2171. ICML 2023Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points
2172. ICML 2023Provable Dynamic Fusion for Low-Quality Multimodal Data
2173. ICML 2023Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP
2174. ICML 2023Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
2175. ICML 2023RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank
2176. ICML 2023Reinforcement Learning Can Be More Efficient with Multiple Rewards
2177. ICML 2023Reinforcement Learning in Low-rank MDPs with Density Features
2178. ICML 2023RLSbench: Domain Adaptation Under Relaxed Label Shift
2179. ICML 2023Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch
2180. ICML 2023Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data
2181. ICML 2023Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability
2182. ICML 2023Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation
2183. ICML 2023Structural Re-weighting Improves Graph Domain Adaptation
2184. ICML 2023SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient
2185. ICML 2023Taxonomy-Structured Domain Adaptation
2186. ICML 2023The Flan Collection: Designing Data and Methods for Effective Instruction Tuning
2187. ICML 2023The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
2188. ICML 2023Theoretical Bounds on the Network Community Profile from Low-rank Semi-definite Programming
2189. ICML 2023Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations
2190. ICML 2023Toward Efficient Gradient-Based Value Estimation
2191. ICML 2023Uncovering Adversarial Risks of Test-Time Adaptation
2192. ICML 2023Using Perturbation to Improve Goodness-of-Fit Tests based on Kernelized Stein Discrepancy
2193. ICML 2023What Can Be Learnt With Wide Convolutional Neural Networks?
2194. ICML 2023Which Tricks are Important for Learning to Rank?
2195. NeurIPS 2023(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
2196. NeurIPS 2023A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression
2197. NeurIPS 2023A Unified Framework for Rank-based Loss Minimization
2198. NeurIPS 2023Adaptive whitening with fast gain modulation and slow synaptic plasticity
2199. NeurIPS 2023Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces
2200. NeurIPS 2023Algorithmic Regularization in Tensor Optimization: Towards a Lifted Approach in Matrix Sensing

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.