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 62 篇,第 1 / 2 页
- CVPR 20255%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks
- CVPR 2025AdaDARE-gamma: Balancing Stability and Plasticity in Multi-modal LLMs through Efficient Adaptation
- CVPR 2025AIpparel: A Multimodal Foundation Model for Digital Garments
- CVPR 2025Argus: A Compact and Versatile Foundation Model for Vision
- CVPR 2025CH3Depth: Efficient and Flexible Depth Foundation Model with Flow Matching
- CVPR 2025Charm: The Missing Piece in ViT Fine-Tuning for Image Aesthetic Assessment
- CVPR 2025CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning
- CVPR 2025COSMIC: Clique-Oriented Semantic Multi-space Integration for Robust CLIP Test-Time Adaptation
- CVPR 2025CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology
- CVPR 2025CustomKD: Customizing Large Vision Foundation for Edge Model Improvement via Knowledge Distillation
- CVPR 2025DEFOM-Stereo: Depth Foundation Model Based Stereo Matching
- CVPR 2025Distilling Monocular Foundation Model for Fine-grained Depth Completion
- CVPR 2025Dynamic Group Normalization: Spatio-Temporal Adaptation to Evolving Data Statistics
- CVPR 2025Efficient Transfer Learning for Video-language Foundation Models
- CVPR 2025Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment
- CVPR 2025F^3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics
- CVPR 2025Faster Parameter-Efficient Tuning with Token Redundancy Reduction
- CVPR 2025Feat2GS: Probing Visual Foundation Models with Gaussian Splatting
- CVPR 2025Fine-Grained Erasure in Text-to-Image Diffusion-based Foundation Models
- CVPR 2025FisherTune: Fisher-Guided Robust Tuning of Vision Foundation Models for Domain Generalized Segmentation
- CVPR 2025FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question Answering
- CVPR 2025FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning
- CVPR 2025HyperFree: A Channel-adaptive and Tuning-free Foundation Model for Hyperspectral Remote Sensing Imagery
- CVPR 2025Interpreting Object-level Foundation Models via Visual Precision Search
- CVPR 2025Label Shift Meets Online Learning: Ensuring Consistent Adaptation with Universal Dynamic Regret
- CVPR 2025Language-Assisted Debiasing and Smoothing for Foundation Model-Based Semi-Supervised Learning
- CVPR 2025Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition
- CVPR 2025Lift3D Policy: Lifting 2D Foundation Models for Robust 3D Robotic Manipulation
- CVPR 2025LoRA Recycle: Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs
- CVPR 2025LoRACLR: Contrastive Adaptation for Customization of Diffusion Models
- CVPR 2025Low-Rank Adaptation in Multilinear Operator Networks for Security-Preserving Incremental Learning
- CVPR 2025Magma: A Foundation Model for Multimodal AI Agents
- CVPR 2025Mamba as a Bridge: Where Vision Foundation Models Meet Vision Language Models for Domain-Generalized Semantic Segmentation
- CVPR 2025Meta-Learning Hyperparameters for Parameter Efficient Fine-Tuning
- CVPR 2025Minimal Interaction Seperated Tuning: A New Paradigm for Visual Adaptation
- CVPR 2025MODfinity: Unsupervised Domain Adaptation with Multimodal Information Flow Intertwining
- CVPR 2025MonoSplat: Generalizable 3D Gaussian Splatting from Monocular Depth Foundation Models
- CVPR 2025OCRT: Boosting Foundation Models in the Open World with Object-Concept-Relation Triad
- CVPR 2025Optimal Transport-Guided Source-Free Adaptation for Face Anti-Spoofing
- CVPR 2025Parameter Efficient Mamba Tuning via Projector-targeted Diagonal-centric Linear Transformation
- CVPR 2025Pioneering 4-Bit FP Quantization for Diffusion Models: Mixup-Sign Quantization and Timestep-Aware Fine-Tuning
- CVPR 2025PointLoRA: Low-Rank Adaptation with Token Selection for Point Cloud Learning
- CVPR 2025Post-pre-training for Modality Alignment in Vision-Language Foundation Models
- CVPR 2025Project-Probe-Aggregate: Efficient Fine-Tuning for Group Robustness
- CVPR 2025Rethinking Token Reduction with Parameter-Efficient Fine-Tuning in ViT for Pixel-Level Tasks
- CVPR 2025Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety
- CVPR 2025Reward Fine-Tuning Two-Step Diffusion Models via Learning Differentiable Latent-Space Surrogate Reward
- CVPR 2025RobSense: A Robust Multi-modal Foundation Model for Remote Sensing with Static, Temporal, and Incomplete Data Adaptability
- CVPR 2025SapiensID: Foundation for Human Recognition
- CVPR 2025SCAP: Transductive Test-Time Adaptation via Supportive Clique-based Attribute Prompting
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。