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 45 of 46

2201. NeurIPS 2023Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization
2202. NeurIPS 2023Bayesian Extensive-Rank Matrix Factorization with Rotational Invariant Priors
2203. NeurIPS 2023Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization
2204. NeurIPS 2023Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models
2205. NeurIPS 2023Combinatorial Optimization with Policy Adaptation using Latent Space Search
2206. NeurIPS 2023Composing Parameter-Efficient Modules with Arithmetic Operation
2207. NeurIPS 2023Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes
2208. NeurIPS 2023Context-lumpable stochastic bandits
2209. NeurIPS 2023Cross-Domain Policy Adaptation via Value-Guided Data Filtering
2210. NeurIPS 2023DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation
2211. NeurIPS 2023Data Selection for Language Models via Importance Resampling
2212. NeurIPS 2023Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence
2213. NeurIPS 2023DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
2214. NeurIPS 2023Efficient Adaptation of Large Vision Transformer via Adapter Re-Composing
2215. NeurIPS 2023Efficient Hyper-parameter Optimization with Cubic Regularization
2216. NeurIPS 2023Efficient Low-rank Backpropagation for Vision Transformer Adaptation
2217. NeurIPS 2023Efficient Model-Free Exploration in Low-Rank MDPs
2218. NeurIPS 2023Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction
2219. NeurIPS 2023Efficient Testable Learning of Halfspaces with Adversarial Label Noise
2220. NeurIPS 2023Errors-in-variables Fr\'echet Regression with Low-rank Covariate Approximation
2221. NeurIPS 2023Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms
2222. NeurIPS 2023Fast Rank-1 Lattice Targeted Sampling for Black-box Optimization
2223. NeurIPS 2023Feature Adaptation for Sparse Linear Regression
2224. NeurIPS 2023Geometric Analysis of Matrix Sensing over Graphs
2225. NeurIPS 2023Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces
2226. NeurIPS 2023Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products
2227. NeurIPS 2023Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
2228. NeurIPS 2023Kissing to Find a Match: Efficient Low-Rank Permutation Representation
2229. NeurIPS 2023Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback
2230. NeurIPS 2023Learning List-Level Domain-Invariant Representations for Ranking
2231. NeurIPS 2023Low Tensor Rank Learning of Neural Dynamics
2232. NeurIPS 2023Lower Bounds on Adaptive Sensing for Matrix Recovery
2233. NeurIPS 2023Matrix Compression via Randomized Low Rank and Low Precision Factorization
2234. NeurIPS 2023Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models
2235. NeurIPS 2023MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates
2236. NeurIPS 2023Multi-Head Adapter Routing for Cross-Task Generalization
2237. NeurIPS 2023Neural Priming for Sample-Efficient Adaptation
2238. NeurIPS 2023Non-Stationary Bandits with Auto-Regressive Temporal Dependency
2239. NeurIPS 2023On the spectral bias of two-layer linear networks
2240. NeurIPS 2023Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
2241. NeurIPS 2023Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing
2242. NeurIPS 2023PDP: Parameter-free Differentiable Pruning is All You Need
2243. NeurIPS 2023Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning
2244. NeurIPS 2023Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent
2245. NeurIPS 2023Progressive Ensemble Distillation: Building Ensembles for Efficient Inference
2246. NeurIPS 2023Provably Efficient Algorithm for Nonstationary Low-Rank MDPs
2247. NeurIPS 2023Q-DM: An Efficient Low-bit Quantized Diffusion Model
2248. NeurIPS 2023QLoRA: Efficient Finetuning of Quantized LLMs
2249. NeurIPS 2023Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization
2250. NeurIPS 2023Rank-DETR for High Quality Object Detection

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.