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

65 papers, page 1 of 2

1. ICML 2023A Three-regime Model of Network Pruning
2. ICML 2023Adversarial Parameter Attack on Deep Neural Networks
3. ICML 2023Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise
4. ICML 2023Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions
5. ICML 2023Bootstrap in High Dimension with Low Computation
6. ICML 2023Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models
7. ICML 2023Curious Replay for Model-based Adaptation
8. ICML 2023Data Efficient Neural Scaling Law via Model Reusing
9. ICML 2023Diffusion Models are Minimax Optimal Distribution Estimators
10. ICML 2023Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning
11. ICML 2023DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule
12. ICML 2023Domain Adaptation for Time Series Under Feature and Label Shifts
13. ICML 2023Double-Weighting for Covariate Shift Adaptation
14. ICML 2023Efficient List-Decodable Regression using Batches
15. ICML 2023Efficient Personalized Federated Learning via Sparse Model-Adaptation
16. ICML 2023ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models
17. ICML 2023Exploring the Benefits of Training Expert Language Models over Instruction Tuning
18. ICML 2023Fast $(1+\varepsilon)$-Approximation Algorithms for Binary Matrix Factorization
19. ICML 2023Flash: Concept Drift Adaptation in Federated Learning
20. ICML 2023Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost
21. ICML 2023Geometric Autoencoders - What You See is What You Decode
22. ICML 2023Hierarchical Imitation Learning with Vector Quantized Models
23. ICML 2023Human-Timescale Adaptation in an Open-Ended Task Space
24. ICML 2023HyperTuning: Toward Adapting Large Language Models without Back-propagation
25. ICML 2023Improved Algorithms for White-Box Adversarial Streams
26. ICML 2023In Search for a Generalizable Method for Source Free Domain Adaptation
27. ICML 2023Last Switch Dependent Bandits with Monotone Payoff Functions
28. ICML 2023Learning in POMDPs is Sample-Efficient with Hindsight Observability
29. ICML 2023Learning-Rate-Free Learning by D-Adaptation
30. ICML 2023LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation
31. ICML 2023Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single
32. ICML 2023Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning
33. ICML 2023Mechanistic Mode Connectivity
34. ICML 2023Multi-User Reinforcement Learning with Low Rank Rewards
35. ICML 2023Naive imputation implicitly regularizes high-dimensional linear models
36. ICML 2023NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning
37. ICML 2023Offline Meta Reinforcement Learning with In-Distribution Online Adaptation
38. ICML 2023On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation
39. ICML 2023On Pitfalls of Test-Time Adaptation
40. ICML 2023On the Role of Attention in Prompt-tuning
41. ICML 2023One-sided Matrix Completion from Two Observations Per Row
42. ICML 2023Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points
43. ICML 2023Provable Dynamic Fusion for Low-Quality Multimodal Data
44. ICML 2023Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP
45. ICML 2023Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
46. ICML 2023RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank
47. ICML 2023Reinforcement Learning Can Be More Efficient with Multiple Rewards
48. ICML 2023Reinforcement Learning in Low-rank MDPs with Density Features
49. ICML 2023RLSbench: Domain Adaptation Under Relaxed Label Shift
50. ICML 2023Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch

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.