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 1,492 篇,第 11 / 30 页
- NeurIPS 2026HandXFM: Semantic-Structural Distillation for Hand Radiograph Foundation Models
- NeurIPS 2026High Performance Differentially Private Fine-Tuning using Dataset Distillation
- NeurIPS 2026How Finite-Rank Bottleneck Shape the Low-Rank Adaptation Landscape
- NeurIPS 2026How Much of a Model Do We Need? Redundancy and Slimmability in Remote Sensing Foundation Models
- NeurIPS 2026Hybrid-LoRA: Bridging Full Fine-Tuning and Low-Rank Adaptation for Post-Training
- NeurIPS 2026Hyperbolic Displacement-Constrained Adaptation for CLIP-Based Class-Incremental Learning
- NeurIPS 2026ImmuVis: Hyperconvolutional Foundation Models for Imaging Mass Cytometry
- NeurIPS 2026Inertia-1: An Open Exploration of Wearable Motion Foundation Models
- NeurIPS 2026IRIS: Interpolative Rényi Iterative Self-play for Large Language Model Fine-Tuning
- NeurIPS 2026Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
- NeurIPS 2026Language-Induced Priors for Domain Adaptation
- NeurIPS 2026Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models
- NeurIPS 2026LEAN: Library-Based Adaptation for Asynchronous, Federated Fine-Tuning
- NeurIPS 2026Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning
- NeurIPS 2026Lift, See, Act: Hierarchical Robot Policy Pretraining with 3D Foundation Models
- NeurIPS 2026LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection
- NeurIPS 2026Mask-Conditioned Gradient Masking for Fine-Tuning Mixture-of-Experts Diffusion Language Models
- NeurIPS 2026MICE: Multi-animal Interaction Context Encoder — A Hierarchical Foundation Model for Mouse Behavior
- NeurIPS 2026Monroe: A Molecular Foundation Model for In-context Probabilistic Inference
- NeurIPS 2026Multimodal Foundation Agents Should Use Brain Data as Privileged Supervision
- NeurIPS 2026Multimodal LLMs Outperform Pathology Foundation Models in Cross-Domain Histological Similarity
- NeurIPS 2026NADS: Navigator-Guided Data Selection for Mitigating Catastrophic Forgetting in Fine-Tuning
- NeurIPS 2026Neuro-KE: Knowledge-Guided Interfaces for Semantically Grounded EEG Foundation Models
- NeurIPS 2026NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces
- NeurIPS 2026NeuroNTP - A Generalizable Multimodal Foundation Model for Epilepsy
- NeurIPS 2026No One Knows the State-of-the-Art in Geospatial Foundation Models
- NeurIPS 2026Nüwa.RNA: An RNA Foundation Model for Unified Representation with Deep Structure Infusion
- NeurIPS 2026OATS: Online Data Augmentation for Time Series Foundation Models
- NeurIPS 2026On the Design Space of Discrete Diffusion Online Adaptation for Molecular Optimization
- NeurIPS 2026One Adapter For All: Towards Generalizable Many-To-One Domain Adaptation In Heterogeneous Collaborative Perception
- NeurIPS 2026One Algorithm, Two Goals: Dual Scoring for Parameter and Data Selection in LLM Fine-Tuning
- NeurIPS 2026One Language-Free Foundation Model Is Enough for Universal Vision Anomaly Detection
- NeurIPS 2026One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
- NeurIPS 2026Online Change-point Detection using Foundation Probabilistic Forecasting Models
- NeurIPS 2026OpenMHC: Accelerating the Science of Wearable Foundation Models
- NeurIPS 2026Optimistic Q-value Adaptation for Offline-to-Online Reinforcement Learning
- NeurIPS 2026OrbitLoRA: Learning Rotation-Aware Low-Data Adaptation of Vision Foundation Models
- NeurIPS 2026PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization
- NeurIPS 2026Pan-FM: A Pan-Organ Foundation Model with Saliency-Guided Masking for Missing Robustness
- NeurIPS 2026Personalized Safety in Federated Fine-Tuning of Large Language Models
- NeurIPS 2026Position: The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models
- NeurIPS 2026Pretraining Curricula Enable Selective Fine-tuning
- NeurIPS 2026PriFT: Prior-Support Guided Token Reweighting for Supervised Fine-Tuning
- NeurIPS 2026PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models
- NeurIPS 2026PRISM: Principal Subspace Alignment for Parameter-Efficient Fine-Tuning
- NeurIPS 2026PROLA: Principal-Orthogonal Low-rank Adaptation for Predictive Spatiotemporal Weather Downscaling
- NeurIPS 2026ProMo3D: Probing Motion Cues in Frozen 3D Foundation Models
- NeurIPS 2026Prysma: Efficient Modality Adaptation for SLO-aware LLM-based Video Question Answering
- NeurIPS 2026RAD-TFM: Robust and Domain-Adapted Tabular Foundation Models
- 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"}
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。