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

95 papers, page 1 of 2

1. ICLR 2024A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
2. ICLR 2024A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data
3. ICLR 2024Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation
4. ICLR 2024Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness
5. ICLR 2024ALAM: Averaged Low-Precision Activation for Memory-Efficient Training of Transformer Models
6. ICLR 2024AlpaGasus: Training a Better Alpaca with Fewer Data
7. ICLR 2024Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
8. ICLR 2024AutoChunk: Automated Activation Chunk for Memory-Efficient Deep Learning Inference
9. ICLR 2024AutoLoRa: An Automated Robust Fine-Tuning Framework
10. ICLR 2024AutoVP: An Automated Visual Prompting Framework and Benchmark
11. ICLR 2024BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation
12. ICLR 2024Batched Low-Rank Adaptation of Foundation Models
13. ICLR 2024Bayesian Low-rank Adaptation for Large Language Models
14. ICLR 2024BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation
15. ICLR 2024Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes
16. ICLR 2024Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages
17. ICLR 2024Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?
18. ICLR 2024CLAP: Collaborative Adaptation for Patchwork Learning
19. ICLR 2024Class Probability Matching with Calibrated Networks for Label Shift Adaption
20. ICLR 2024Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation
21. ICLR 2024Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
22. ICLR 2024Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning
23. ICLR 2024DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models
24. ICLR 2024Debiasing Algorithm through Model Adaptation
25. ICLR 2024DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
26. ICLR 2024Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks
27. ICLR 2024Dissecting learning and forgetting in language model finetuning
28. ICLR 2024DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning
29. ICLR 2024Dynamic Layer Tying for Parameter-Efficient Transformers
30. ICLR 2024Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization
31. ICLR 2024EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models
32. ICLR 2024Enhancing Neural Training via a Correlated Dynamics Model
33. ICLR 2024Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow
34. ICLR 2024FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
35. ICLR 2024Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
36. ICLR 2024First-order ANIL provably learns representations despite overparametrisation
37. ICLR 2024Gradual Domain Adaptation via Gradient Flow
38. ICLR 2024Implicit bias of SGD in $L_2$-regularized linear DNNs: One-way jumps from high to low rank
39. ICLR 2024Implicit Neural Representation Inference for Low-Dimensional Bayesian Deep Learning
40. ICLR 2024Improving LoRA in Privacy-preserving Federated Learning
41. ICLR 2024Improving Non-Transferable Representation Learning by Harnessing Content and Style
42. ICLR 2024Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
43. ICLR 2024Koopman-based generalization bound: New aspect for full-rank weights
44. ICLR 2024Learning Conditional Invariances through Non-Commutativity
45. ICLR 2024Learning Hierarchical Polynomials with Three-Layer Neural Networks
46. ICLR 2024Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning
47. ICLR 2024Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
48. ICLR 2024LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero-initialized Attention
49. ICLR 2024LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units
50. ICLR 2024LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models

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.