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 6 of 11

251. ICLR 2025LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
252. ICLR 2025LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning
253. ICLR 2025LoLCATs: On Low-Rank Linearizing of Large Language Models
254. ICLR 2025Long-Context Linear System Identification
255. ICLR 2025LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation
256. ICLR 2025LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
257. ICLR 2025LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
258. ICLR 2025LoRA-X: Bridging Foundation Models with Training-Free Cross-Model Adaptation
259. ICLR 2025LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation models
260. ICLR 2025LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning
261. ICLR 2025Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning
262. ICLR 2025MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba
263. ICLR 2025Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
264. ICLR 2025MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projection
265. ICLR 2025MCNC: Manifold-Constrained Reparameterization for Neural Compression
266. ICLR 2025Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering
267. ICLR 2025MeteoRA: Multiple-tasks Embedded LoRA for Large Language Models
268. ICLR 2025MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling
269. ICLR 2025MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture of Shards
270. ICLR 2025MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion
271. ICLR 2025MTSAM: Multi-Task Fine-Tuning for Segment Anything Model
272. ICLR 2025NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance
273. ICLR 2025Noisy Test-Time Adaptation in Vision-Language Models
274. ICLR 2025OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition
275. ICLR 2025On Large Language Model Continual Unlearning
276. ICLR 2025On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning
277. ICLR 2025On the Benefits of Attribute-Driven Graph Domain Adaptation
278. ICLR 2025On the Crucial Role of Initialization for Matrix Factorization
279. ICLR 2025On the Optimization Landscape of Low Rank Adaptation Methods for Large Language Models
280. ICLR 2025PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
281. ICLR 2025Palu: KV-Cache Compression with Low-Rank Projection
282. ICLR 2025PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction
283. ICLR 2025Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization
284. ICLR 2025Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences
285. ICLR 2025Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents
286. ICLR 2025pMoE: Prompting Diverse Experts Together Wins More in Visual Adaptation
287. ICLR 2025PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches
288. ICLR 2025Progressive Parameter Efficient Transfer Learning for Semantic Segmentation
289. ICLR 2025Proxy Denoising for Source-Free Domain Adaptation
290. ICLR 2025QERA: an Analytical Framework for Quantization Error Reconstruction
291. ICLR 2025Quantum-PEFT: Ultra parameter-efficient fine-tuning
292. ICLR 2025R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference
293. ICLR 2025RandLoRA: Full rank parameter-efficient fine-tuning of large models
294. ICLR 2025RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
295. ICLR 2025RaSA: Rank-Sharing Low-Rank Adaptation
296. ICLR 2025Re-Imagining Multimodal Instruction Tuning: A Representation View
297. ICLR 2025RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks
298. ICLR 2025Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA
299. ICLR 2025Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts
300. ICLR 2025SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation

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.