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 602 篇,第 12 / 13 页
- NeurIPS 2026RAHF: Reward-Amplified Human Feedback for Closed-Loop Policy Fine-Tuning
- NeurIPS 2026Raw-Routed Mixture of Adapters: A Causal Intervention for Routing Collapse in Time Series Foundation Models
- NeurIPS 2026RayTun3R: Online Camera Adaptation in 3D Foundation Models
- NeurIPS 2026Reasoning-Trace Collapse: Evaluating the Loss of Explicit Reasoning During Fine-Tuning
- NeurIPS 2026Relation-Aware Graph Foundation Model
- NeurIPS 2026Resource-Aware Parameter-Efficient Model Adaptation for Onboard High-Dimensional Data
- NeurIPS 2026Rest-Tuning: Data-Efficient Adaptation of EEG Foundation Models to Individuals via Resting-State Signals
- NeurIPS 2026Rethinking "RL Generalizes, SFT Memorizes": The Role of SFT Data
- NeurIPS 2026Rethinking LLM Fine-Tuning via Weight Space Reparameterization: Preserving Safety during Downstream Adaptation
- NeurIPS 2026RIZZ: Routing Interactions to Near Zero-Interference Zones for Continual Adaptation of Black-Box Agents
- NeurIPS 2026Robust and Efficient Finetuning of Vision Foundation Models via Implicit Ensembling
- NeurIPS 2026Robust Diffusion Models via Divergence-Induced Weighted Denoising
- NeurIPS 2026SaMA: Morpho Adaptation via Asymmetric Expansion of Kronecker Product
- NeurIPS 2026SapiensID 2.0: Aligning Human Recognition Foundation Models with Human Perception
- NeurIPS 2026Scalable Adaptation of 3D Geometric Foundation Models via Weak Supervision from Internet Video
- NeurIPS 2026Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters
- NeurIPS 2026ScreenShot: A Foundation Model for Few-Shot Combination Drug Screening
- NeurIPS 2026SDS-LoRA: Overcoming Anisotropic Gradient Scaling in Low-Rank Adaptation
- NeurIPS 2026SLDR: Defending Against Malicious Fine-tuning via Selective Layers Recovery and Dynamic Routing
- NeurIPS 2026Solver-as-Teacher: Solver-Guided On-Policy Post-Training Framework for PDE Foundation Models
- NeurIPS 2026SPIRIT: Speed-Driven Online Adaptation for Self-Speculative Decoding
- NeurIPS 2026Stability Regimes for Framing-Sensitive Fine-Tuning in Language Models
- NeurIPS 2026Tabular Foundation Model for Generative Modelling
- NeurIPS 2026TACO: Towards Task-Consistent Open-Vocabulary Adaptation in Video Recognition
- NeurIPS 2026Tadpole: Autoencoders as Foundation Models for 3D PDEs with Online Learning
- NeurIPS 2026The Geometry of Alignment Collapse: When Fine-Tuning Breaks Safety
- NeurIPS 2026The Optimal Control Foundation of Early Exits – Turnpikes and ResNets
- NeurIPS 2026The Surprising Effectiveness of Deleting Weights in LLM Reasoning and Adaptation
- NeurIPS 2026Towards Identifying Dominant Low-Rank Subspaces in Zeroth-Order Fine-Tuning
- NeurIPS 2026Towards Reconstructing Geographically Diverse Architecture with 3D Foundation Models
- NeurIPS 2026Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning
- NeurIPS 2026Trust the Direction, Search the Step: Zero-and-First-Order Methods for LLM Fine-Tuning
- NeurIPS 2026TS-ICL: A Flexible Time-Indexed Foundation Model for Time Series via In-Context Learning
- NeurIPS 2026Tune-Up Open-Weight CLIP: Optimization Framework for Self-Supervised Fine-tuning of CLIP
- NeurIPS 2026Tuning the Tuner
- NeurIPS 2026U-MOF: Uncertainty-Guided Parameter-Efficient Multi-Objective Fine-Tuning for Long-Tailed Recognition
- NeurIPS 2026Uncertainty-Aware Listwise Reinforcement Fine-Tuning for Fine-Grained Visual Classification
- NeurIPS 2026Unified Panoramic Geometry Estimation via Multi-View Foundation Models
- NeurIPS 2026Unveiling Implicit Advantage Symmetry: Why GRPO Struggles with Exploration and Difficulty Adaptation
- NeurIPS 2026Vibe-Spike: An Energy-Preserving EEG Foundation Model Through the Landscape of Neural Coherence
- NeurIPS 2026What DNA Foundation Models Learn Beyond Sequence Composition
- NeurIPS 2026What do EEG Foundation Models Capture from Human Brain Signals?
- NeurIPS 2026What Does an Observability Forecasting Foundation Model Know?
- NeurIPS 2026What Drives Test-Time Adaptation for CLIP? A Controlled Empirical Study from an Update Perspective
- NeurIPS 2026When Catastrophic Inheritance Meets Forgetting in Continual Adaptation of Foundation Models
- NeurIPS 2026When does LeJEPA learn a World Model?
- NeurIPS 2026When the Merge Coefficient Stops Mattering: Proximity Regularized Merging for Continual LoRA Adaptation
- NeurIPS 2026When to Trust a PFN: Detecting Harmful Shift in Tabular Foundation Models
- NeurIPS 2026Where Do We (Not) Need Temporal Context in Low-Resource Video Task Adaptation?
- NeurIPS 2026Where You Backpropagate Matters: Token Hypothesis for Memory-Efficient 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。