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

531 papers, page 5 of 11

201. NeurIPS 2025Brain Harmony: A Multimodal Foundation Model Unifying Morphology and Function into 1D Tokens
202. NeurIPS 2025BrainMoE: Cognition Joint Embedding via Mixture-of-Expert Towards Robust Brain Foundation Model
203. NeurIPS 2025BrainOmni: A Brain Foundation Model for Unified EEG and MEG Signals
204. NeurIPS 2025C-LoRA: Contextual Low-Rank Adaptation for Uncertainty Estimation in Large Language Models
205. NeurIPS 2025Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmark
206. NeurIPS 2025Can LLMs Reason Over Non-Text Modalities in a Training-Free Manner? A Case Study with In-Context Representation Learning
207. NeurIPS 2025CF-VLM：CounterFactual Vision-Language Fine-tuning
208. NeurIPS 2025ChromFound: Towards A Universal Foundation Model for Single-Cell Chromatin Accessibiltiy Data
209. NeurIPS 2025Class-aware Domain Knowledge Fusion and Fission for Continual Test-Time Adaptation
210. NeurIPS 2025Compress to Impress: Efficient LLM Adaptation Using a Single Gradient Step on 100 Samples
211. NeurIPS 2025Correlated Low-Rank Adaptation for ConvNets
212. NeurIPS 2025CrossSpectra: Exploiting Cross-Layer Smoothness for Parameter-Efficient Fine-Tuning
213. NeurIPS 2025CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding
214. NeurIPS 2025Curvature Tuning: Provable Training-free Model Steering From a Single Parameter
215. NeurIPS 2025Data Efficient Adaptation in Large Language Models via Continuous Low-Rank Fine-Tuning
216. NeurIPS 2025Deep Gaussian from Motion: Exploring 3D Geometric Foundation Models for Gaussian Splatting
217. NeurIPS 2025Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models
218. NeurIPS 2025DEFT: Decompositional Efficient Fine-Tuning for Text-to-Image Models
219. NeurIPS 2025Demystifying Network Foundation Models
220. NeurIPS 2025Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
221. NeurIPS 2025Distribution-Aligned Decoding for Efficient LLM Task Adaptation
222. NeurIPS 2025Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data
223. NeurIPS 2025DLoFT: Gradient-Decoupled Fine-Tuning for Generalizable Long Chain-of-Thought Reasoning
224. NeurIPS 2025DOTA: Distributional Test-time Adaptation of Vision-Language Models
225. NeurIPS 2025DP-LLM: Runtime Model Adaptation with Dynamic Layer-wise Precision Assignment
226. NeurIPS 2025Dual Prototype-Enhanced Contrastive Framework for Class-Imbalanced Graph Domain Adaptation
227. NeurIPS 2025E-BATS: Efficient Backpropagation-Free Test-Time Adaptation for Speech Foundation Models
228. NeurIPS 2025Efficient Data Selection at Scale via Influence Distillation
229. NeurIPS 2025Efficient Randomized Experiments Using Foundation Models
230. NeurIPS 2025Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models
231. NeurIPS 2025EMLoC: Emulator-based Memory-efficient Fine-tuning with LoRA Correction
232. NeurIPS 2025Enhanced Expert Merging for Mixture-of-Experts in Graph Foundation Models
233. NeurIPS 2025Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size
234. NeurIPS 2025Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation
235. NeurIPS 2025EquiTabPFN: A Target-Permutation Equivariant Prior Fitted Network
236. NeurIPS 2025Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models
237. NeurIPS 2025F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
238. NeurIPS 2025FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic
239. NeurIPS 2025Fantastic Features and Where to Find Them: A Probing Method to combine Features from Multiple Foundation Models
240. NeurIPS 2025Fast and Fluent Diffusion Language Models via Convolutional Decoding and Rejective Fine-tuning
241. NeurIPS 2025Fin3R: Fine-tuning Feed-forward 3D Reconstruction Models via Monocular Knowledge Distillation
242. NeurIPS 2025FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models
243. NeurIPS 2025FlyLoRA: Boosting Task Decoupling and Parameter Efficiency via Implicit Rank-Wise Mixture-of-Experts
244. NeurIPS 2025Fourier Analysis Network
245. NeurIPS 2025From Pretraining to Pathology: How Noise Leads to Catastrophic Inheritance in Medical Models
246. NeurIPS 2025Gains: Fine-grained Federated Domain Adaptation in Open Set
247. NeurIPS 2025GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation
248. NeurIPS 2025Gated Integration of Low-Rank Adaptation for Continual Learning of Large Language Models
249. NeurIPS 2025Generating Informative Samples for Risk-Averse Fine-Tuning of Downstream Tasks
250. NeurIPS 2025GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters

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.