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

632 papers, page 6 of 13

251. ICLR 2025Unified Parameter-Efficient Unlearning for LLMs
252. ICLR 2025Unleashing the Power of Task-Specific Directions in Parameter Efficient Fine-tuning
253. ICLR 2025Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning
254. ICLR 2025Utilitarian Algorithm Configuration for Infinite Parameter Spaces
255. ICLR 2025ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models
256. ICML 2025A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
257. ICML 2025A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
258. ICML 2025All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance
259. ICML 2025Approximation to Smooth Functions by Low-Rank Swish Networks
260. ICML 2025Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
261. ICML 2025Autonomy-of-Experts Models
262. ICML 2025Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning
263. ICML 2025Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
264. ICML 2025BSLoRA: Enhancing the Parameter Efficiency of LoRA with Intra-Layer and Inter-Layer Sharing
265. ICML 2025Byzantine-Resilient Federated Alternating Gradient Descent and Minimization for Partly-Decoupled Low Rank Matrix Learning
266. ICML 2025Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers
267. ICML 2025CLOVER: Cross-Layer Orthogonal Vectors Pruning
268. ICML 2025Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation
269. ICML 2025Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe Method
270. ICML 2025Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
271. ICML 2025Compute or Load KV Cache? Why Not Both?
272. ICML 2025COSDA: Counterfactual-based Susceptibility Risk Framework for Open-Set Domain Adaptation
273. ICML 2025Customizing the Inductive Biases of Softmax Attention using Structured Matrices
274. ICML 2025Disentangled Graph Spectral Domain Adaptation
275. ICML 2025Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
276. ICML 2025Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering
277. ICML 2025DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation
278. ICML 2025Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning
279. ICML 2025Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
280. ICML 2025Efficient Network Automatic Relevance Determination
281. ICML 2025Efficient Personalized Adaptation for Physiological Signal Foundation Model
282. ICML 2025Ehrenfeucht-Haussler Rank and Chain of Thought
283. ICML 2025ELoRA: Low-Rank Adaptation for Equivariant GNNs
284. ICML 2025Exploiting Presentative Feature Distributions for Parameter-Efficient Continual Learning of Large Language Models
285. ICML 2025ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts
286. ICML 2025Fast and Low-Cost Genomic Foundation Models via Outlier Removal
287. ICML 2025Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation
288. ICML 2025Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning Framework
289. ICML 2025Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
290. ICML 2025Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
291. ICML 2025From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications
292. ICML 2025From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control
293. ICML 2025FRUGAL: Memory-Efficient Optimization by Reducing State Overhead for Scalable Training
294. ICML 2025Function-Space Learning Rates
295. ICML 2025GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression
296. ICML 2025GLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric Algebras
297. ICML 2025GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration
298. ICML 2025Grokking Beyond the Euclidean Norm of Model Parameters
299. ICML 2025GS-Bias: Global-Spatial Bias Learner for Single-Image Test-Time Adaptation of Vision-Language Models
300. ICML 2025Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery

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.