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

76 papers, page 1 of 2

1. ICLR 2023A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias
2. ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
3. ICLR 2023A General Rank Preserving Framework for Asymmetric Image Retrieval
4. ICLR 2023Achieving Near-Optimal Individual Regret & Low Communications in Multi-Agent Bandits
5. ICLR 2023Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
6. ICLR 2023Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation
7. ICLR 2023AnyDA: Anytime Domain Adaptation
8. ICLR 2023Approximate Nearest Neighbor Search through Modern Error-Correcting Codes
9. ICLR 2023Basic Binary Convolution Unit for Binarized Image Restoration Network
10. ICLR 2023Block and Subword-Scaling Floating-Point (BSFP) : An Efficient Non-Uniform Quantization For Low Precision Inference
11. ICLR 2023Characterizing the spectrum of the NTK via a power series expansion
12. ICLR 2023Consolidator: Mergable Adapter with Group Connections for Visual Adaptation
13. ICLR 2023Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning
14. ICLR 2023Decision S4: Efficient Sequence-Based RL via State Spaces Layers
15. ICLR 2023Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation
16. ICLR 2023DELTA: DEGRADATION-FREE FULLY TEST-TIME ADAPTATION
17. ICLR 2023Dirichlet-based Uncertainty Calibration for Active Domain Adaptation
18. ICLR 2023Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors
19. ICLR 2023Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach
20. ICLR 2023Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation
21. ICLR 2023DynaMS: Dyanmic Margin Selection for Efficient Deep Learning
22. ICLR 2023Effective Self-supervised Pre-training on Low-compute Networks without Distillation
23. ICLR 2023Efficient Conditionally Invariant Representation Learning
24. ICLR 2023Efficient Deep Reinforcement Learning Requires Regulating Overfitting
25. ICLR 2023Efficient Edge Inference by Selective Query
26. ICLR 2023Embedding Fourier for Ultra-High-Definition Low-Light Image Enhancement
27. ICLR 2023Energy-Based Test Sample Adaptation for Domain Generalization
28. ICLR 2023ESD: Expected Squared Difference as a Tuning-Free Trainable Calibration Measure
29. ICLR 2023Exploring Low-Rank Property in Multiple Instance Learning for Whole Slide Image Classification
30. ICLR 2023Feature selection and low test error in shallow low-rotation ReLU networks
31. ICLR 2023Few-Shot Domain Adaptation For End-to-End Communication
32. ICLR 2023FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification
33. ICLR 2023HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing
34. ICLR 2023Hyper-Decision Transformer for Efficient Online Policy Adaptation
35. ICLR 2023IDEAL: Query-Efficient Data-Free Learning from Black-Box Models
36. ICLR 2023Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data
37. ICLR 2023Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions
38. ICLR 2023Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs
39. ICLR 2023In-Situ Text-Only Adaptation of Speech Models with Low-Overhead Speech Imputations
40. ICLR 2023Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation
41. ICLR 2023KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Low-Resource NLP
42. ICLR 2023Latent State Marginalization as a Low-cost Approach for Improving Exploration
43. ICLR 2023Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets
44. ICLR 2023Learning Sparse and Low-Rank Priors for Image Recovery via Iterative Reweighted Least Squares Minimization
45. ICLR 2023Learning the Positions in CountSketch
46. ICLR 2023Lossless Adaptation of Pretrained Vision Models For Robotic Manipulation
47. ICLR 2023M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation
48. ICLR 2023MECTA: Memory-Economic Continual Test-Time Model Adaptation
49. ICLR 2023Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform
50. ICLR 2023Moving Forward by Moving Backward: Embedding Action Impact over Action Semantics

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.