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

每年论文数

各会议论文数

按年份和会议统计

基础模型适配论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202381183624159
202494507056270
20251741497662461
202618218714291602

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

全部基础模型适配论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 531 篇，第 5 / 11 页

  1. NeurIPS 2025Brain Harmony: A Multimodal Foundation Model Unifying Morphology and Function into 1D Tokens
  2. NeurIPS 2025BrainMoE: Cognition Joint Embedding via Mixture-of-Expert Towards Robust Brain Foundation Model
  3. NeurIPS 2025BrainOmni: A Brain Foundation Model for Unified EEG and MEG Signals
  4. NeurIPS 2025C-LoRA: Contextual Low-Rank Adaptation for Uncertainty Estimation in Large Language Models
  5. NeurIPS 2025Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmark
  6. NeurIPS 2025Can LLMs Reason Over Non-Text Modalities in a Training-Free Manner? A Case Study with In-Context Representation Learning
  7. NeurIPS 2025CF-VLM：CounterFactual Vision-Language Fine-tuning
  8. NeurIPS 2025ChromFound: Towards A Universal Foundation Model for Single-Cell Chromatin Accessibiltiy Data
  9. NeurIPS 2025Class-aware Domain Knowledge Fusion and Fission for Continual Test-Time Adaptation
  10. NeurIPS 2025Compress to Impress: Efficient LLM Adaptation Using a Single Gradient Step on 100 Samples
  11. NeurIPS 2025Correlated Low-Rank Adaptation for ConvNets
  12. NeurIPS 2025CrossSpectra: Exploiting Cross-Layer Smoothness for Parameter-Efficient Fine-Tuning
  13. NeurIPS 2025CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding
  14. NeurIPS 2025Curvature Tuning: Provable Training-free Model Steering From a Single Parameter
  15. NeurIPS 2025Data Efficient Adaptation in Large Language Models via Continuous Low-Rank Fine-Tuning
  16. NeurIPS 2025Deep Gaussian from Motion: Exploring 3D Geometric Foundation Models for Gaussian Splatting
  17. NeurIPS 2025Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models
  18. NeurIPS 2025DEFT: Decompositional Efficient Fine-Tuning for Text-to-Image Models
  19. NeurIPS 2025Demystifying Network Foundation Models
  20. NeurIPS 2025Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
  21. NeurIPS 2025Distribution-Aligned Decoding for Efficient LLM Task Adaptation
  22. NeurIPS 2025Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data
  23. NeurIPS 2025DLoFT: Gradient-Decoupled Fine-Tuning for Generalizable Long Chain-of-Thought Reasoning
  24. NeurIPS 2025DOTA: Distributional Test-time Adaptation of Vision-Language Models
  25. NeurIPS 2025DP-LLM: Runtime Model Adaptation with Dynamic Layer-wise Precision Assignment
  26. NeurIPS 2025Dual Prototype-Enhanced Contrastive Framework for Class-Imbalanced Graph Domain Adaptation
  27. NeurIPS 2025E-BATS: Efficient Backpropagation-Free Test-Time Adaptation for Speech Foundation Models
  28. NeurIPS 2025Efficient Data Selection at Scale via Influence Distillation
  29. NeurIPS 2025Efficient Randomized Experiments Using Foundation Models
  30. NeurIPS 2025Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models
  31. NeurIPS 2025EMLoC: Emulator-based Memory-efficient Fine-tuning with LoRA Correction
  32. NeurIPS 2025Enhanced Expert Merging for Mixture-of-Experts in Graph Foundation Models
  33. NeurIPS 2025Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size
  34. NeurIPS 2025Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation
  35. NeurIPS 2025EquiTabPFN: A Target-Permutation Equivariant Prior Fitted Network
  36. NeurIPS 2025Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models
  37. NeurIPS 2025F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
  38. NeurIPS 2025FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic
  39. NeurIPS 2025Fantastic Features and Where to Find Them: A Probing Method to combine Features from Multiple Foundation Models
  40. NeurIPS 2025Fast and Fluent Diffusion Language Models via Convolutional Decoding and Rejective Fine-tuning
  41. NeurIPS 2025Fin3R: Fine-tuning Feed-forward 3D Reconstruction Models via Monocular Knowledge Distillation
  42. NeurIPS 2025FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models
  43. NeurIPS 2025FlyLoRA: Boosting Task Decoupling and Parameter Efficiency via Implicit Rank-Wise Mixture-of-Experts
  44. NeurIPS 2025Fourier Analysis Network
  45. NeurIPS 2025From Pretraining to Pathology: How Noise Leads to Catastrophic Inheritance in Medical Models
  46. NeurIPS 2025Gains: Fine-grained Federated Domain Adaptation in Open Set
  47. NeurIPS 2025GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation
  48. NeurIPS 2025Gated Integration of Low-Rank Adaptation for Continual Learning of Large Language Models
  49. NeurIPS 2025Generating Informative Samples for Risk-Averse Fine-Tuning of Downstream Tasks
  50. NeurIPS 2025GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters

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"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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