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 602 篇，第 11 / 13 页

  1. NeurIPS 2026HandXFM: Semantic-Structural Distillation for Hand Radiograph Foundation Models
  2. NeurIPS 2026High Performance Differentially Private Fine-Tuning using Dataset Distillation
  3. NeurIPS 2026How Finite-Rank Bottleneck Shape the Low-Rank Adaptation Landscape
  4. NeurIPS 2026How Much of a Model Do We Need? Redundancy and Slimmability in Remote Sensing Foundation Models
  5. NeurIPS 2026Hybrid-LoRA: Bridging Full Fine-Tuning and Low-Rank Adaptation for Post-Training
  6. NeurIPS 2026Hyperbolic Displacement-Constrained Adaptation for CLIP-Based Class-Incremental Learning
  7. NeurIPS 2026ImmuVis: Hyperconvolutional Foundation Models for Imaging Mass Cytometry
  8. NeurIPS 2026Inertia-1: An Open Exploration of Wearable Motion Foundation Models
  9. NeurIPS 2026IRIS: Interpolative Rényi Iterative Self-play for Large Language Model Fine-Tuning
  10. NeurIPS 2026Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
  11. NeurIPS 2026Language-Induced Priors for Domain Adaptation
  12. NeurIPS 2026Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models
  13. NeurIPS 2026LEAN: Library-Based Adaptation for Asynchronous, Federated Fine-Tuning
  14. NeurIPS 2026Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning
  15. NeurIPS 2026Lift, See, Act: Hierarchical Robot Policy Pretraining with 3D Foundation Models
  16. NeurIPS 2026LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection
  17. NeurIPS 2026Mask-Conditioned Gradient Masking for Fine-Tuning Mixture-of-Experts Diffusion Language Models
  18. NeurIPS 2026MICE: Multi-animal Interaction Context Encoder — A Hierarchical Foundation Model for Mouse Behavior
  19. NeurIPS 2026Monroe: A Molecular Foundation Model for In-context Probabilistic Inference
  20. NeurIPS 2026Multimodal Foundation Agents Should Use Brain Data as Privileged Supervision
  21. NeurIPS 2026Multimodal LLMs Outperform Pathology Foundation Models in Cross-Domain Histological Similarity
  22. NeurIPS 2026NADS: Navigator-Guided Data Selection for Mitigating Catastrophic Forgetting in Fine-Tuning
  23. NeurIPS 2026Neuro-KE: Knowledge-Guided Interfaces for Semantically Grounded EEG Foundation Models
  24. NeurIPS 2026NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces
  25. NeurIPS 2026NeuroNTP - A Generalizable Multimodal Foundation Model for Epilepsy
  26. NeurIPS 2026No One Knows the State-of-the-Art in Geospatial Foundation Models
  27. NeurIPS 2026Nüwa.RNA: An RNA Foundation Model for Unified Representation with Deep Structure Infusion
  28. NeurIPS 2026OATS: Online Data Augmentation for Time Series Foundation Models
  29. NeurIPS 2026On the Design Space of Discrete Diffusion Online Adaptation for Molecular Optimization
  30. NeurIPS 2026One Adapter For All: Towards Generalizable Many-To-One Domain Adaptation In Heterogeneous Collaborative Perception
  31. NeurIPS 2026One Algorithm, Two Goals: Dual Scoring for Parameter and Data Selection in LLM Fine-Tuning
  32. NeurIPS 2026One Language-Free Foundation Model Is Enough for Universal Vision Anomaly Detection
  33. NeurIPS 2026One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
  34. NeurIPS 2026Online Change-point Detection using Foundation Probabilistic Forecasting Models
  35. NeurIPS 2026OpenMHC: Accelerating the Science of Wearable Foundation Models
  36. NeurIPS 2026Optimistic Q-value Adaptation for Offline-to-Online Reinforcement Learning
  37. NeurIPS 2026OrbitLoRA: Learning Rotation-Aware Low-Data Adaptation of Vision Foundation Models
  38. NeurIPS 2026PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization
  39. NeurIPS 2026Pan-FM: A Pan-Organ Foundation Model with Saliency-Guided Masking for Missing Robustness
  40. NeurIPS 2026Personalized Safety in Federated Fine-Tuning of Large Language Models
  41. NeurIPS 2026Position: The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models
  42. NeurIPS 2026Pretraining Curricula Enable Selective Fine-tuning
  43. NeurIPS 2026PriFT: Prior-Support Guided Token Reweighting for Supervised Fine-Tuning
  44. NeurIPS 2026PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models
  45. NeurIPS 2026PRISM: Principal Subspace Alignment for Parameter-Efficient Fine-Tuning
  46. NeurIPS 2026PROLA: Principal-Orthogonal Low-rank Adaptation for Predictive Spatiotemporal Weather Downscaling
  47. NeurIPS 2026ProMo3D: Probing Motion Cues in Frozen 3D Foundation Models
  48. NeurIPS 2026Prysma: Efficient Modality Adaptation for SLO-aware LLM-based Video Question Answering
  49. NeurIPS 2026RAD-TFM: Robust and Domain-Adapted Tabular Foundation Models
  50. NeurIPS 2026RadOmni: Advancing Foundation Model for Non-contrast CT with Omni Radiology Knowledge

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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