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

565 papers, page 5 of 12

201. ICML 2026Task-Driven Subspace Decomposition for Knowledge Sharing and Isolation in LoRA-based Continual Learning
202. ICML 2026Tempora: Characterising the Time-Contingent Utility of Online Test-Time Adaptation
203. ICML 2026TetraJet-v2: Accurate NVFP4 Training for Large Language Models with Oscillation Suppression and Outlier Control
204. ICML 2026The Appeal and Reality of Recycling LoRAs with Adaptive Merging
205. ICML 2026The Expressive Power of Low Precision Softmax Transformers with (Summarized) Chain-of-Thought
206. ICML 2026The Geometry of Narrow Fine-Tuning Degradation: Trajectory Lock-in and Spectral Bifurcation
207. ICML 2026The Geometry of Updates: Fisher Alignment at Vocabulary Scale
208. ICML 2026Theory of Minimal Weight Perturbations in Deep Networks and its Applications for Low-Rank Activated Backdoor Attacks
209. ICML 2026TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling
210. ICML 2026TokenDrop: Token-Level Importance-Aware Backward Propagation Skipping for Efficient LLM Fine-Tuning
211. ICML 2026TopAdapter: Topology-Aware Prompt Tuning for Efficient Point Cloud Understanding
212. ICML 2026Toward Robust Multilingual Adaptation of LLMs for Low-Resource Languages
213. ICML 2026Towards Understanding the Dynamics of Low-Rank Adaptation
214. ICML 2026TPV: Parameter Perturbations Through the Lens of Test Prediction Variance
215. ICML 2026Training-Free Adaptation of Diffusion Models via Doob's $h$-Transform
216. ICML 2026Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment
217. ICML 2026Transport Clustering: Solving Low-Rank Optimal Transport via Clustering
218. ICML 2026Transport or Discard: Robust Unbalanced Optimal Transport for Cross-Domain Policy Adaptation
219. ICML 2026Tucker Attention: A generalization of approximate attention mechanisms
220. ICML 2026Turning Back Without Forgetting: Selective Backward Refinement for Parameter-Efficient Continual Learning
221. ICML 2026TWLA: Achieving Ternary Weights and Low-Bit Activations for LLMs via Post-Training Quantization
222. ICML 2026U$^3$CF: Unbiased, Unconfounding, and Unified Causal Framework for Multi-Target Domain Adaptation
223. ICML 2026UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models
224. ICML 2026Ultrafast On-Chip Online Learning via Spline Locality in Kolmogorov–Arnold Networks
225. ICML 2026Understanding Catastrophic Forgetting In LoRA via Mean-Field Attention Dynamics
226. ICML 2026Understanding LoRA as Knowledge Memory: An Empirical Analysis
227. ICML 2026UnHype: CLIP-Guided Hypernetworks for Dynamic LoRA Unlearning
228. ICML 2026Unifying Low Dimensional Spectra in Deep Learning
229. ICML 2026UniSVQ: 2-bit Unified Scalar-Vector Quantization
230. ICML 2026Video-SVD: Efficient Video Diffusion via Orthogonal Basis Composition
231. ICML 2026Weight Updates as Activation Shifts: A Principled Framework for Steering
232. ICML 2026What Makes Value Learning Efficient in Residual Reinforcement Learning?
233. ICML 2026What Reward Structure Enables Efficient Sparse-Reward RL? A Proof-of-Concept with Policy-Aware Matrix Completion
234. ICML 2026When Does Adaptation Win? Scaling Laws for Meta-Learning in Quantum Control
235. ICML 2026When Is Rank-1 Enough? Geometry-Guided Initialization for Parameter-Efficient Fine-Tuning
236. ICML 2026When More Data Doesn't Help: Limits of Adaptation in Multitask Learning
237. ICML 2026WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
238. ICML 2026Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation
239. ICML 2026xKV: Cross-Layer KV-Cache Compression via Aligned Singular Vector Extraction
240. ICML 2026Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression
241. ICML 2025A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
242. ICML 2025A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
243. ICML 2025All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance
244. ICML 2025Approximation to Smooth Functions by Low-Rank Swish Networks
245. ICML 2025Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
246. ICML 2025Autonomy-of-Experts Models
247. ICML 2025Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning
248. ICML 2025Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
249. ICML 2025BSLoRA: Enhancing the Parameter Efficiency of LoRA with Intra-Layer and Inter-Layer Sharing
250. ICML 2025Byzantine-Resilient Federated Alternating Gradient Descent and Minimization for Partly-Decoupled Low Rank Matrix Learning

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.