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 152 篇，第 1 / 4 页

1. ICLR 2025$InterLCM$: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration
2. ICLR 2025A Differentiable Rank-Based Objective for Better Feature Learning
3. ICLR 2025A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning
4. ICLR 2025Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
5. ICLR 2025Adaptive Rank Allocation: Speeding Up Modern Transformers with RaNA Adapters
6. ICLR 2025AdaRankGrad: Adaptive Gradient Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning
7. ICLR 2025Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models
8. ICLR 2025ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
9. ICLR 2025An Efficient Framework for Crediting Data Contributors of Diffusion Models
10. ICLR 2025Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation
11. ICLR 2025Binary Losses for Density Ratio Estimation
12. ICLR 2025BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
13. ICLR 2025Black Sheep in the Herd: Playing with Spuriously Correlated Attributes for Vision-Language Recognition
14. ICLR 2025Block-Attention for Efficient Prefilling
15. ICLR 2025Cached Multi-Lora Composition for Multi-Concept Image Generation
16. ICLR 2025Can LLMs Really Learn to Translate a Low-Resource Language from One Grammar Book?
17. ICLR 2025CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models
18. ICLR 2025CBQ: Cross-Block Quantization for Large Language Models
19. ICLR 2025Closed-Form Merging of Parameter-Efficient Modules for Federated Continual Learning
20. ICLR 2025COAT: Compressing Optimizer states and Activations for Memory-Efficient FP8 Training
21. ICLR 2025ComLoRA: A Competitive Learning Approach for Enhancing LoRA
22. ICLR 2025Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models
23. ICLR 2025Continual Slow-and-Fast Adaptation of Latent Neural Dynamics (CoSFan): Meta-Learning What-How & When to Adapt
24. ICLR 2025Continuous Exposure Learning for Low-light Image Enhancement using Neural ODEs
25. ICLR 2025CtrLoRA: An Extensible and Efficient Framework for Controllable Image Generation
26. ICLR 2025DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models
27. ICLR 2025DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
28. ICLR 2025dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation
29. ICLR 2025Decoupling Angles and Strength in Low-rank Adaptation
30. ICLR 2025DELIFT: Data Efficient Language model Instruction Fine-Tuning
31. ICLR 2025Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration
32. ICLR 2025Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives
33. ICLR 2025Does SGD really happen in tiny subspaces?
34. ICLR 2025Dynamic Low-Rank Sparse Adaptation for Large Language Models
35. ICLR 2025Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
36. ICLR 2025DynaPrompt: Dynamic Test-Time Prompt Tuning
37. ICLR 2025Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation
38. ICLR 2025Efficient and Context-Aware Label Propagation for Zero-/Few-Shot Training-Free Adaptation of Vision-Language Model
39. ICLR 2025Efficient Learning with Sine-Activated Low-Rank Matrices
40. ICLR 2025Efficient Low-Bit Quantization with Adaptive Scales for Multi-Task Co-Training
41. ICLR 2025Efficient Model Editing with Task-Localized Sparse Fine-tuning
42. ICLR 2025Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data
43. ICLR 2025Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement
44. ICLR 2025Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning
45. ICLR 2025Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures
46. ICLR 2025Ensembles of Low-Rank Expert Adapters
47. ICLR 2025Estimating the Probabilities of Rare Outputs in Language Models
48. ICLR 2025Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models
49. ICLR 2025Federated Residual Low-Rank Adaptation of Large Language Models
50. ICLR 2025Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment

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。