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
- 基础模型适配论文从 2023 年的 159 篇增长到 2026 年的 602 篇，三年间扩大到约 3.8 倍。
- NeurIPS 是发基础模型适配论文最多的会议，2023–2026 年共 531 篇，占四个会议总量的 36%。
- 交叉方向里涨得最快的是深度学习 · foundation models：同时属于两个主题的论文从 2023 年的 7 篇增至 2026 年的 66 篇。
- 在「元学习与迁移」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的持续学习是 1.7 倍，基础模型适配是 3.8 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 81 | 18 | 36 | 24 | 159 |
| 2024 | 94 | 50 | 70 | 56 | 270 |
| 2025 | 174 | 149 | 76 | 62 | 461 |
| 2026 | 182 | 187 | 142 | 91 | 602 |
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(Mis)generalization of Helpful-Only Fine-Tuning
- ICML 2026Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance
- ICLR 2026Benchmarking ECG Foundational Models: A Reality Check Across Clinical Tasks
- CVPR 2026CD-Buffer Complementary Dual-Buffer Framework for Test-Time Adaptation in Adverse Weather
- NeurIPS 2025An Investigation of Memorization Risk in Healthcare Foundation Models
- ICML 2025A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
- ICLR 2025Better autoregressive regression with LLMs via regression-aware fine-tuning
- CVPR 20255%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks
- NeurIPS 2024Instruction Tuning Large Language Models to Understand Electronic Health Records
- ICML 2024By Tying Embeddings You Are Assuming the Distributional Hypothesis
- ICLR 2024A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
- CVPR 2024DePT: Decoupled Prompt Tuning
- NeurIPS 2023A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging
- ICML 2023Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations
- ICLR 2023A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias
- CVPR 2023A-La-Carte Prompt Tuning (APT): Combining Distinct Data via Composable Prompting
- NeurIPS 2026A Graph Foundation Model for Unified Clustering
- ICML 2026AdaMeZO: Adam-style Zeroth-Order Optimizer for LLM Fine-tuning Without Maintaining the Moments
- ICLR 2026Bridging Radiology and Pathology Foundation Models via Concept-Based Multimodal Co-Adaptation
- CVPR 2026Fed-ADE Adaptive Learning Rate for Federated Post-adaptation under Distribution Shift
全部基础模型适配论文
共 270 篇，第 6 / 6 页
- NeurIPS 2024Source Code Foundation Models are Transferable Binary Analysis Knowledge Bases
- NeurIPS 2024Spectral Adapter: Fine-Tuning in Spectral Space
- NeurIPS 2024Stepping Forward on the Last Mile
- NeurIPS 2024Stress-Testing Capability Elicitation With Password-Locked Models
- NeurIPS 2024Style Adaptation and Uncertainty Estimation for Multi-Source Blended-Target Domain Adaptation
- NeurIPS 2024SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors
- NeurIPS 2024Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models
- NeurIPS 2024Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
- NeurIPS 2024The Impact of Initialization on LoRA Finetuning Dynamics
- NeurIPS 2024The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models
- NeurIPS 2024Towards Calibrated Robust Fine-Tuning of Vision-Language Models
- NeurIPS 2024Uncertainty-aware Fine-tuning of Segmentation Foundation Models
- NeurIPS 2024Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective
- NeurIPS 2024UniDSeg: Unified Cross-Domain 3D Semantic Segmentation via Visual Foundation Models Prior
- NeurIPS 2024Unveiling LoRA Intrinsic Ranks via Salience Analysis
- NeurIPS 2024Vaccine: Perturbation-aware Alignment for Large Language Models against Harmful Fine-tuning Attack
- NeurIPS 2024VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks
- NeurIPS 2024Vision Foundation Model Enables Generalizable Object Pose Estimation
- NeurIPS 2024What does guidance do? A fine-grained analysis in a simple setting
- NeurIPS 2024WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management Tasks
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"}
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。