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 124 篇，第 1 / 3 页

1. ICML 20243D Geometric Shape Assembly via Efficient Point Cloud Matching
2. ICML 2024A Closer Look at the Limitations of Instruction Tuning
3. ICML 2024A Tensor Decomposition Perspective on Second-order RNNs
4. ICML 2024Adaptively Learning to Select-Rank in Online Platforms
5. ICML 2024Allocation Requires Prediction Only if Inequality Is Low
6. ICML 2024AMPA: Adaptive Mixed Precision Allocation for Low-Bit Integer Training
7. ICML 2024Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs
8. ICML 2024APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
9. ICML 2024AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA
10. ICML 2024Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications
11. ICML 2024Asymmetry in Low-Rank Adapters of Foundation Models
12. ICML 2024Batch Singular Value Polarization and Weighted Semantic Augmentation for Universal Domain Adaptation
13. ICML 2024Bayesian Adaptation of Network Depth and Width for Continual Learning
14. ICML 2024BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
15. ICML 2024Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
16. ICML 2024Category-Aware Active Domain Adaptation
17. ICML 2024CauDiTS: Causal Disentangled Domain Adaptation of Multivariate Time Series
18. ICML 2024Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
19. ICML 2024Collage: Light-Weight Low-Precision Strategy for LLM Training
20. ICML 2024CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations
21. ICML 2024Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
22. ICML 2024Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation
23. ICML 2024Cross-Domain Policy Adaptation by Capturing Representation Mismatch
24. ICML 2024Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
25. ICML 2024Debiased Distribution Compression
26. ICML 2024Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics
27. ICML 2024Differentiable Weightless Neural Networks
28. ICML 2024Differentially Private Domain Adaptation with Theoretical Guarantees
29. ICML 2024DiJiang: Efficient Large Language Models through Compact Kernelization
30. ICML 2024DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models
31. ICML 2024Do Efficient Transformers Really Save Computation?
32. ICML 2024DoRA: Weight-Decomposed Low-Rank Adaptation
33. ICML 2024DPZero: Private Fine-Tuning of Language Models without Backpropagation
34. ICML 2024E$^2$GAN: Efficient Training of Efficient GANs for Image-to-Image Translation
35. ICML 2024EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Error Rank Minimization
36. ICML 2024Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning
37. ICML 2024Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
38. ICML 2024Efficient Non-stationary Online Learning by Wavelets with Applications to Online Distribution Shift Adaptation
39. ICML 2024Efficient Pareto Manifold Learning with Low-Rank Structure
40. ICML 2024Energy-Efficient Gaussian Processes Using Low-Precision Arithmetic
41. ICML 2024Error Feedback Can Accurately Compress Preconditioners
42. ICML 2024ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections
43. ICML 2024Evaluation of Test-Time Adaptation Under Computational Time Constraints
44. ICML 2024Exploring the Low-Pass Filtering Behavior in Image Super-Resolution
45. ICML 2024Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
46. ICML 2024Fast White-Box Adversarial Streaming Without a Random Oracle
47. ICML 2024Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training
48. ICML 2024FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models
49. ICML 2024Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes
50. ICML 2024FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees

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。