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 461 篇,第 4 / 10 页
- ICLR 2025nGPT: Normalized Transformer with Representation Learning on the Hypersphere
- ICLR 2025NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals
- ICLR 2025NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval
- ICLR 2025On the Optimization Landscape of Low Rank Adaptation Methods for Large Language Models
- ICLR 2025PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
- ICLR 2025PEARL: Towards Permutation-Resilient LLMs
- ICLR 2025PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches
- ICLR 2025Preserving Diversity in Supervised Fine-Tuning of Large Language Models
- ICLR 2025ProteinBench: A Holistic Evaluation of Protein Foundation Models
- ICLR 2025Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning
- ICLR 2025QERA: an Analytical Framework for Quantization Error Reconstruction
- ICLR 2025Quantized Spike-driven Transformer
- ICLR 2025Quantum-PEFT: Ultra parameter-efficient fine-tuning
- ICLR 2025RaSA: Rank-Sharing Low-Rank Adaptation
- ICLR 2025RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation
- ICLR 2025Re-Imagining Multimodal Instruction Tuning: A Representation View
- ICLR 2025RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks
- ICLR 2025Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon
- ICLR 2025Reconstructive Visual Instruction Tuning
- ICLR 2025Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer
- ICLR 2025Revisiting Convolution Architecture in the Realm of DNA Foundation Models
- ICLR 2025Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts
- ICLR 2025ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL
- ICLR 2025RRM: Robust Reward Model Training Mitigates Reward Hacking
- ICLR 2025SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation
- ICLR 2025SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation
- ICLR 2025Scaling Diffusion Language Models via Adaptation from Autoregressive Models
- ICLR 2025Scaling Wearable Foundation Models
- ICLR 2025SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning
- ICLR 2025SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection
- ICLR 2025Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer
- ICLR 2025Selective Aggregation for Low-Rank Adaptation in Federated Learning
- ICLR 2025Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs
- ICLR 2025Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency
- ICLR 2025Should VLMs be Pre-trained with Image Data?
- ICLR 2025SMT: Fine-Tuning Large Language Models with Sparse Matrices
- ICLR 2025Sparse autoencoders reveal selective remapping of visual concepts during adaptation
- ICLR 2025Specialized Foundation Models Struggle to Beat Supervised Baselines
- ICLR 2025Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent Flows
- ICLR 2025SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks
- ICLR 2025STAFF: Speculative Coreset Selection for Task-Specific Fine-tuning
- ICLR 2025STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs
- ICLR 2025Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling
- ICLR 2025TC-MoE: Augmenting Mixture of Experts with Ternary Expert Choice
- ICLR 2025Teaching LLMs How to Learn with Contextual Fine-Tuning
- ICLR 2025Tell me about yourself: LLMs are aware of their learned behaviors
- ICLR 2025To Code or Not To Code? Exploring Impact of Code in Pre-training
- ICLR 2025Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy Hessians
- ICLR 2025Towards Foundation Models for Mixed Integer Linear Programming
- ICLR 2025Training-Free Activation Sparsity in Large Language Models
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。