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 1,492 篇，第 25 / 30 页

  1. ICML 2024LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
  2. ICML 2024Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning
  3. ICML 2024Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
  4. ICML 2024LoRA Training in the NTK Regime has No Spurious Local Minima
  5. ICML 2024LoRA+: Efficient Low Rank Adaptation of Large Models
  6. ICML 2024MOMENT: A Family of Open Time-series Foundation Models
  7. ICML 2024Not all distributional shifts are equal: Fine-grained robust conformal inference
  8. ICML 2024On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis
  9. ICML 2024Open-Vocabulary Calibration for Fine-tuned CLIP
  10. ICML 2024Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
  11. ICML 2024Parameter-Efficient Fine-Tuning with Controls
  12. ICML 2024Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
  13. ICML 2024Position: Foundation Agents as the Paradigm Shift for Decision Making
  14. ICML 2024Position: Graph Foundation Models Are Already Here
  15. ICML 2024Position: On the Societal Impact of Open Foundation Models
  16. ICML 2024Position: Why Tabular Foundation Models Should Be a Research Priority
  17. ICML 2024Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
  18. ICML 2024Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
  19. ICML 2024Prompting a Pretrained Transformer Can Be a Universal Approximator
  20. ICML 2024Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models
  21. ICML 2024Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
  22. ICML 2024Recovering the Pre-Fine-Tuning Weights of Generative Models
  23. ICML 2024Reducing Fine-Tuning Memory Overhead by Approximate and Memory-Sharing Backpropagation
  24. ICML 2024Revisiting the Power of Prompt for Visual Tuning
  25. ICML 2024Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models
  26. ICML 2024Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
  27. ICML 2024RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation
  28. ICML 2024Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models
  29. ICML 2024SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation
  30. ICML 2024Selecting Large Language Model to Fine-tune via Rectified Scaling Law
  31. ICML 2024Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
  32. ICML 2024Sparse is Enough in Fine-tuning Pre-trained Large Language Models
  33. ICML 2024SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
  34. ICML 2024SuDA: Support-based Domain Adaptation for Sim2Real Hinge Joint Tracking with Flexible Sensors
  35. ICML 2024To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO
  36. ICML 2024Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention
  37. ICML 2024Transferring Knowledge From Large Foundation Models to Small Downstream Models
  38. ICML 2024Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts
  39. ICML 2024Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models
  40. NeurIPS 2024A Hitchhiker's Guide to Fine-Grained Face Forgery Detection Using Common Sense Reasoning
  41. NeurIPS 2024A Simple yet Universal Framework for Depth Completion
  42. NeurIPS 2024B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory
  43. NeurIPS 2024BackdoorAlign: Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment
  44. NeurIPS 2024Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models
  45. NeurIPS 2024BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
  46. NeurIPS 2024Brain-JEPA: Brain Dynamics Foundation Model with Gradient Positioning and Spatiotemporal Masking
  47. NeurIPS 2024Cell ontology guided transcriptome foundation model
  48. NeurIPS 2024Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees
  49. NeurIPS 2024CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for Task-Aware Parameter-Efficient Fine-tuning
  50. NeurIPS 2024Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise

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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