Foundation Model Adaptation papers, 2023–2026

Key findings

• Foundation Model Adaptation went from 159 papers in 2023 to 602 in 2026, roughly 3.8x in three years.
• NeurIPS publishes the most Foundation Model Adaptation work: 531 papers from 2023 to 2026, 36% of the four-venue total.
• The fastest-growing overlap is with Deep learning · foundation models: papers tagged with both rose from 7 in 2023 to 66 in 2026.
• Among the 5 topics under Meta-Learning and Transfer, it ranks #1 by 2026 paper count; the fastest grower in the group, Continual Learning, is up 1.7x versus 3.8x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Foundation Model Adaptation papers

24 papers, page 1 of 1

1. CVPR 2023A-La-Carte Prompt Tuning (APT): Combining Distinct Data via Composable Prompting
2. CVPR 2023Boosting Transductive Few-Shot Fine-Tuning With Margin-Based Uncertainty Weighting and Probability Regularization
3. CVPR 2023Divide and Adapt: Active Domain Adaptation via Customized Learning
4. CVPR 2023Fine-Grained Face Swapping via Regional GAN Inversion
5. CVPR 2023Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation
6. CVPR 2023Guided Recommendation for Model Fine-Tuning
7. CVPR 2023Hint-Aug: Drawing Hints From Foundation Vision Transformers Towards Boosted Few-Shot Parameter-Efficient Tuning
8. CVPR 2023Integral Neural Networks
9. CVPR 2023Integrally Pre-Trained Transformer Pyramid Networks
10. CVPR 2023Masked Images Are Counterfactual Samples for Robust Fine-Tuning
11. CVPR 2023MELTR: Meta Loss Transformer for Learning To Fine-Tune Video Foundation Models
12. CVPR 2023MetaPortrait: Identity-Preserving Talking Head Generation With Fast Personalized Adaptation
13. CVPR 2023MHPL: Minimum Happy Points Learning for Active Source Free Domain Adaptation
14. CVPR 2023MOT: Masked Optimal Transport for Partial Domain Adaptation
15. CVPR 2023Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation
16. CVPR 2023Policy Adaptation From Foundation Model Feedback
17. CVPR 2023Prompt, Generate, Then Cache: Cascade of Foundation Models Makes Strong Few-Shot Learners
18. CVPR 2023Semi-Supervised Domain Adaptation With Source Label Adaptation
19. CVPR 2023Test Time Adaptation With Regularized Loss for Weakly Supervised Salient Object Detection
20. CVPR 2023Towards Better Stability and Adaptability: Improve Online Self-Training for Model Adaptation in Semantic Segmentation
21. CVPR 2023Towards Fast Adaptation of Pretrained Contrastive Models for Multi-Channel Video-Language Retrieval
22. CVPR 2023Train/Test-Time Adaptation With Retrieval
23. CVPR 2023Trainable Projected Gradient Method for Robust Fine-Tuning
24. CVPR 2023TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization

FAQ

How many Foundation Model Adaptation papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,492 in total: 159 in 2023, 270 in 2024, 461 in 2025, 602 in 2026.

How many Foundation Model Adaptation papers are at NeurIPS 2026?

NeurIPS 2026 has 182 Foundation Model Adaptation papers, versus 174 the year before.

How many Foundation Model Adaptation papers are at ICLR 2026?

ICLR 2026 has 187 Foundation Model Adaptation papers, versus 149 the year before.

How many Foundation Model Adaptation papers are at ICML 2026?

ICML 2026 has 142 Foundation Model Adaptation papers, versus 76 the year before.

How many Foundation Model Adaptation papers are at CVPR 2026?

CVPR 2026 has 91 Foundation Model Adaptation papers, versus 62 the year before.

Which conference publishes the most Foundation Model Adaptation papers?

NeurIPS, with 531 papers from 2023 to 2026.