低秩适配论文趋势 2023–2026

LoRA 与参数高效微调

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 2,273 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

低秩适配论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202378766563282
202419395124106518
2025241152136103632
2026269184240148841

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

全部低秩适配论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 2,272 篇，第 22 / 46 页

  1. ICLR 2025R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference
  2. ICLR 2025RandLoRA: Full rank parameter-efficient fine-tuning of large models
  3. ICLR 2025RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
  4. ICLR 2025RaSA: Rank-Sharing Low-Rank Adaptation
  5. ICLR 2025Re-Imagining Multimodal Instruction Tuning: A Representation View
  6. ICLR 2025RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks
  7. ICLR 2025Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA
  8. ICLR 2025Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts
  9. ICLR 2025SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation
  10. ICLR 2025SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation
  11. ICLR 2025Scalable Decentralized Learning with Teleportation
  12. ICLR 2025Scaling Transformers for Low-Bitrate High-Quality Speech Coding
  13. ICLR 2025SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning
  14. ICLR 2025SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection
  15. ICLR 2025Selective Aggregation for Low-Rank Adaptation in Federated Learning
  16. ICLR 2025Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency
  17. ICLR 2025SEPARATE: A Simple Low-rank Projection for Gradient Compression in Modern Large-scale Model Training Process
  18. ICLR 2025Shallow diffusion networks provably learn hidden low-dimensional structure
  19. ICLR 2025Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions
  20. ICLR 2025Skill Expansion and Composition in Parameter Space
  21. ICLR 2025SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs
  22. ICLR 2025Smoothing the Shift: Towards Stable Test-Time Adaptation under Complex Multimodal Noises
  23. ICLR 2025SMT: Fine-Tuning Large Language Models with Sparse Matrices
  24. ICLR 2025SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG
  25. ICLR 2025SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning
  26. ICLR 2025Surprising Effectiveness of pretraining Ternary Language Model at Scale
  27. ICLR 2025SVDQuant: Absorbing Outliers by Low-Rank Component for 4-Bit Diffusion Models
  28. ICLR 2025TabM: Advancing tabular deep learning with parameter-efficient ensembling
  29. ICLR 2025Test-Time Adaptation for Combating Missing Modalities in Egocentric Videos
  30. ICLR 2025Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
  31. ICLR 2025The Unreasonable Ineffectiveness of the Deeper Layers
  32. ICLR 2025Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs
  33. ICLR 2025Towards Robust Multimodal Open-set Test-time Adaptation via Adaptive Entropy-aware Optimization
  34. ICLR 2025Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning
  35. ICLR 2025Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
  36. ICLR 2025Transformers Learn Low Sensitivity Functions: Investigations and Implications
  37. ICLR 2025TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram
  38. ICLR 2025Tuning Frequency Bias of State Space Models
  39. ICLR 2025Two Sparse Matrices are Better than One: Sparsifying Neural Networks with Double Sparse Factorization
  40. ICLR 2025u-$\mu$P: The Unit-Scaled Maximal Update Parametrization
  41. ICLR 2025Unified Parameter-Efficient Unlearning for LLMs
  42. ICLR 2025Unleashing the Power of Task-Specific Directions in Parameter Efficient Fine-tuning
  43. ICLR 2025Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning
  44. ICLR 2025Utilitarian Algorithm Configuration for Infinite Parameter Spaces
  45. ICLR 2025ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models
  46. ICML 2025A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
  47. ICML 2025A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
  48. ICML 2025All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance
  49. ICML 2025Approximation to Smooth Functions by Low-Rank Swish Networks
  50. ICML 2025Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查低秩适配在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？

AI 会调用的工具：get_topic_stats {"topic": "low-rank-adaptation"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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