基础模型适配论文趋势 2023–2026

微调与适配

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,492 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

基础模型适配论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202381183624159
202494507056270
20251741497662461
202618218714291602

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

全部基础模型适配论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 76 篇，第 1 / 2 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 2025Adapting to Evolving Adversaries with Regularized Continual Robust Training
  4. ICML 2025AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
  5. ICML 2025Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
  6. ICML 2025Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety
  7. ICML 2025Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions
  8. ICML 2025Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
  9. ICML 2025Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between Samples
  10. ICML 2025Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers
  11. ICML 2025Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation
  12. ICML 2025Contextures: Representations from Contexts
  13. ICML 2025Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
  14. ICML 2025Efficient Personalized Adaptation for Physiological Signal Foundation Model
  15. ICML 2025ELoRA: Low-Rank Adaptation for Equivariant GNNs
  16. ICML 2025Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization
  17. ICML 2025Enhancing Foundation Models with Federated Domain Knowledge Infusion
  18. ICML 2025ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts
  19. ICML 2025Fast and Low-Cost Genomic Foundation Models via Outlier Removal
  20. ICML 2025Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
  21. ICML 2025Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset Selection
  22. ICML 2025From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control
  23. ICML 2025GAPrompt: Geometry-Aware Point Cloud Prompt for 3D Vision Model
  24. ICML 2025Griffin: Towards a Graph-Centric Relational Database Foundation Model
  25. ICML 2025In-Context Adaptation to Concept Drift for Learned Database Operations
  26. ICML 2025In-Context Fine-Tuning for Time-Series Foundation Models
  27. ICML 2025InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective
  28. ICML 2025Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning
  29. ICML 2025L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning
  30. ICML 2025Large Continual Instruction Assistant
  31. ICML 2025Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning
  32. ICML 2025Lightweight Online Adaption for Time Series Foundation Model Forecasts
  33. ICML 2025LoRA Training Provably Converges to a Low-Rank Global Minimum Or It Fails Loudly (But it Probably Won't Fail)
  34. ICML 2025MixMin: Finding Data Mixtures via Convex Minimization
  35. ICML 2025Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
  36. ICML 2025NextCoder: Robust Adaptation of Code LMs to Diverse Code Edits
  37. ICML 2025OmniArch: Building Foundation Model for Scientific Computing
  38. ICML 2025On Fine-Grained Distinct Element Estimation
  39. ICML 2025Parameter-Efficient Fine-Tuning of State Space Models
  40. ICML 2025Peri-LN: Revisiting Normalization Layer in the Transformer Architecture
  41. ICML 2025PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction
  42. ICML 2025Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
  43. ICML 2025Projection Pursuit Density Ratio Estimation
  44. ICML 2025Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models
  45. ICML 2025Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent
  46. ICML 2025Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting
  47. ICML 2025Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
  48. ICML 2025RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts
  49. ICML 2025Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach
  50. ICML 2025Rethinking the Bias of Foundation Model under Long-tailed Distribution

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 查基础模型适配在 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": "foundation-model-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基础模型适配论文？
共 1,492 篇，按年份分别是 2023 年 159 篇、2024 年 270 篇、2025 年 461 篇、2026 年 602 篇。
NeurIPS 2026 有多少篇基础模型适配论文？
NeurIPS 2026 有 182 篇基础模型适配论文，上一届是 174 篇。
ICLR 2026 有多少篇基础模型适配论文？
ICLR 2026 有 187 篇基础模型适配论文，上一届是 149 篇。
ICML 2026 有多少篇基础模型适配论文？
ICML 2026 有 142 篇基础模型适配论文，上一届是 76 篇。
CVPR 2026 有多少篇基础模型适配论文？
CVPR 2026 有 91 篇基础模型适配论文，上一届是 62 篇。
哪个会议的基础模型适配论文最多？
NeurIPS，2023–2026 年共 531 篇。

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