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

159 papers, page 3 of 4

101. NeurIPS 2023Equivariant Adaptation of Large Pretrained Models
102. NeurIPS 2023Exact recovery and Bregman hard clustering of node-attributed Stochastic Block Model
103. NeurIPS 2023Fast Trainable Projection for Robust Fine-tuning
104. NeurIPS 2023Feature Adaptation for Sparse Linear Regression
105. NeurIPS 2023Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
106. NeurIPS 2023FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing
107. NeurIPS 2023Foundation Model is Efficient Multimodal Multitask Model Selector
108. NeurIPS 2023Generalized Logit Adjustment: Calibrating Fine-tuned Models by Removing Label Bias in Foundation Models
109. NeurIPS 2023Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation
110. NeurIPS 2023Geodesic Multi-Modal Mixup for Robust Fine-Tuning
111. NeurIPS 2023Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design
112. NeurIPS 2023GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction
113. NeurIPS 2023HiBug: On Human-Interpretable Model Debug
114. NeurIPS 2023Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data
115. NeurIPS 2023How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization
116. NeurIPS 2023HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution
117. NeurIPS 2023Importance-aware Co-teaching for Offline Model-based Optimization
118. NeurIPS 2023Inner-Outer Aware Reconstruction Model for Monocular 3D Scene Reconstruction
119. NeurIPS 2023Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision
120. NeurIPS 2023Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning
121. NeurIPS 2023Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation
122. NeurIPS 2023MixFormerV2: Efficient Fully Transformer Tracking
123. NeurIPS 2023Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation
124. NeurIPS 2023Model Shapley: Equitable Model Valuation with Black-box Access
125. NeurIPS 2023Model Sparsity Can Simplify Machine Unlearning
126. NeurIPS 2023Model-enhanced Vector Index
127. NeurIPS 2023Moment Matching Denoising Gibbs Sampling
128. NeurIPS 2023MoVie: Visual Model-Based Policy Adaptation for View Generalization
129. NeurIPS 2023Near-Optimal $k$-Clustering in the Sliding Window Model
130. NeurIPS 2023On Sparse Modern Hopfield Model
131. NeurIPS 2023On the Connection between Pre-training Data Diversity and Fine-tuning Robustness
132. NeurIPS 2023Optimal Transport Model Distributional Robustness
133. NeurIPS 2023OV-PARTS: Towards Open-Vocabulary Part Segmentation
134. NeurIPS 2023Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
135. NeurIPS 2023PIXIU: A Comprehensive Benchmark, Instruction Dataset and Large Language Model for Finance
136. NeurIPS 2023Preference-grounded Token-level Guidance for Language Model Fine-tuning
137. NeurIPS 2023R-divergence for Estimating Model-oriented Distribution Discrepancy
138. NeurIPS 2023RDumb: A simple approach that questions our progress in continual test-time adaptation
139. NeurIPS 2023Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone
140. NeurIPS 2023Retaining Beneficial Information from Detrimental Data for Neural Network Repair
141. NeurIPS 2023Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards
142. NeurIPS 2023SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process
143. NeurIPS 2023Self-Chained Image-Language Model for Video Localization and Question Answering
144. NeurIPS 2023SPA: A Graph Spectral Alignment Perspective for Domain Adaptation
145. NeurIPS 2023Subspace Identification for Multi-Source Domain Adaptation
146. NeurIPS 2023Synthetic-to-Real Pose Estimation with Geometric Reconstruction
147. NeurIPS 2023Task-Robust Pre-Training for Worst-Case Downstream Adaptation
148. NeurIPS 2023The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs
149. NeurIPS 2023TIES-Merging: Resolving Interference When Merging Models
150. NeurIPS 2023To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis

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.