低秩适配论文趋势 2023–2026

主要结论

• 低秩适配论文从 2023 年的 282 篇增长到 2026 年的 841 篇，三年间扩大到约 3.0 倍。
• NeurIPS 是发低秩适配论文最多的会议，2023–2026 年共 781 篇，占四个会议总量的 34%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 4 篇增至 2026 年的 61 篇。
• 在「优化与缩放」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的缩放定律是 4.1 倍，低秩适配是 3.0 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部低秩适配论文

共 136 篇，第 1 / 3 页

1. ICML 2025A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
2. ICML 2025A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
3. ICML 2025All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance
4. ICML 2025Approximation to Smooth Functions by Low-Rank Swish Networks
5. ICML 2025Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
6. ICML 2025Autonomy-of-Experts Models
7. ICML 2025Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning
8. ICML 2025Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
9. ICML 2025BSLoRA: Enhancing the Parameter Efficiency of LoRA with Intra-Layer and Inter-Layer Sharing
10. ICML 2025Byzantine-Resilient Federated Alternating Gradient Descent and Minimization for Partly-Decoupled Low Rank Matrix Learning
11. ICML 2025Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers
12. ICML 2025CLOVER: Cross-Layer Orthogonal Vectors Pruning
13. ICML 2025Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation
14. ICML 2025Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe Method
15. ICML 2025Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
16. ICML 2025Compute or Load KV Cache? Why Not Both?
17. ICML 2025COSDA: Counterfactual-based Susceptibility Risk Framework for Open-Set Domain Adaptation
18. ICML 2025Customizing the Inductive Biases of Softmax Attention using Structured Matrices
19. ICML 2025Disentangled Graph Spectral Domain Adaptation
20. ICML 2025Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
21. ICML 2025Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering
22. ICML 2025DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation
23. ICML 2025Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning
24. ICML 2025Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
25. ICML 2025Efficient Network Automatic Relevance Determination
26. ICML 2025Efficient Personalized Adaptation for Physiological Signal Foundation Model
27. ICML 2025Ehrenfeucht-Haussler Rank and Chain of Thought
28. ICML 2025ELoRA: Low-Rank Adaptation for Equivariant GNNs
29. ICML 2025Exploiting Presentative Feature Distributions for Parameter-Efficient Continual Learning of Large Language Models
30. ICML 2025ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts
31. ICML 2025Fast and Low-Cost Genomic Foundation Models via Outlier Removal
32. ICML 2025Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation
33. ICML 2025Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning Framework
34. ICML 2025Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
35. ICML 2025Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
36. ICML 2025From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications
37. ICML 2025From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control
38. ICML 2025FRUGAL: Memory-Efficient Optimization by Reducing State Overhead for Scalable Training
39. ICML 2025Function-Space Learning Rates
40. ICML 2025GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression
41. ICML 2025GLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric Algebras
42. ICML 2025GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration
43. ICML 2025Grokking Beyond the Euclidean Norm of Model Parameters
44. ICML 2025GS-Bias: Global-Spatial Bias Learner for Single-Image Test-Time Adaptation of Vision-Language Models
45. ICML 2025Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
46. ICML 2025H-Tuning: Toward Low-Cost and Efficient ECG-based Cardiovascular Disease Detection with Pre-Trained Models
47. ICML 2025HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation
48. ICML 2025Hierarchical Masked Autoregressive Models with Low-Resolution Token Pivots
49. ICML 2025Hierarchical Refinement: Optimal Transport to Infinity and Beyond
50. ICML 2025High-Dimensional Tensor Regression With Oracle Properties

常见问题

2023–2026 年四大会议一共有多少篇低秩适配论文？

共 2,273 篇，按年份分别是 2023 年 282 篇、2024 年 518 篇、2025 年 632 篇、2026 年 841 篇。

NeurIPS 2026 有多少篇低秩适配论文？

NeurIPS 2026 有 269 篇低秩适配论文，上一届是 241 篇。

ICLR 2026 有多少篇低秩适配论文？

ICLR 2026 有 184 篇低秩适配论文，上一届是 152 篇。

ICML 2026 有多少篇低秩适配论文？

ICML 2026 有 240 篇低秩适配论文，上一届是 136 篇。

CVPR 2026 有多少篇低秩适配论文？

CVPR 2026 有 148 篇低秩适配论文，上一届是 103 篇。

哪个会议的低秩适配论文最多？

NeurIPS，2023–2026 年共 781 篇。