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

461 papers, page 4 of 10

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

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.