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

404 papers, page 5 of 9

201. ICLR 2025Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models
202. ICLR 2025CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts
203. ICLR 2025CryoFM: A Flow-based Foundation Model for Cryo-EM Densities
204. ICLR 2025CTSyn: A Foundation Model for Cross Tabular Data Generation
205. ICLR 2025DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
206. ICLR 2025dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation
207. ICLR 2025Decoupling Angles and Strength in Low-rank Adaptation
208. ICLR 2025DELIFT: Data Efficient Language model Instruction Fine-Tuning
209. ICLR 2025Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
210. ICLR 2025Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models
211. ICLR 2025Does Spatial Cognition Emerge in Frontier Models?
212. ICLR 2025DRESSing Up LLM: Efficient Stylized Question-Answering via Style Subspace Editing
213. ICLR 2025Dynamic Low-Rank Sparse Adaptation for Large Language Models
214. ICLR 2025DynaPrompt: Dynamic Test-Time Prompt Tuning
215. ICLR 2025Efficient Model Editing with Task-Localized Sparse Fine-tuning
216. ICLR 2025Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
217. ICLR 2025Emergence of meta-stable clustering in mean-field transformer models
218. ICLR 2025Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models
219. ICLR 2025Encryption-Friendly LLM Architecture
220. ICLR 2025Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Data
221. ICLR 2025Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning
222. ICLR 2025Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures
223. ICLR 2025Ensembles of Low-Rank Expert Adapters
224. ICLR 2025Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models
225. ICLR 2025Federated Residual Low-Rank Adaptation of Large Language Models
226. ICLR 2025Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic
227. ICLR 2025Fine-tuning can Help Detect Pretraining Data from Large Language Models
228. ICLR 2025Fine-tuning with Reserved Majority for Noise Reduction
229. ICLR 2025Forget the Data and Fine-Tuning! Just Fold the Network to Compress
230. ICLR 2025Fundamental Limitations on Subquadratic Alternatives to Transformers
231. ICLR 2025Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency
232. ICLR 2025Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
233. ICLR 2025Generative Representational Instruction Tuning
234. ICLR 2025GeoLoRA: Geometric integration for parameter efficient fine-tuning
235. ICLR 2025GOAL: A Generalist Combinatorial Optimization Agent Learner
236. ICLR 2025HiRA: Parameter-Efficient Hadamard High-Rank Adaptation for Large Language Models
237. ICLR 2025Hyper-Connections
238. ICLR 2025Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
239. ICLR 2025Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning
240. ICLR 2025Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models
241. ICLR 2025Intervening Anchor Token: Decoding Strategy in Alleviating Hallucinations for MLLMs
242. ICLR 2025Jamba: Hybrid Transformer-Mamba Language Models
243. ICLR 2025KaSA: Knowledge-Aware Singular-Value Adaptation of Large Language Models
244. ICLR 2025Knowledge Graph Finetuning Enhances Knowledge Manipulation in Large Language Models
245. ICLR 2025Kolmogorov-Arnold Transformer
246. ICLR 2025Large Convolutional Model Tuning via Filter Subspace
247. ICLR 2025Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning
248. ICLR 2025Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation
249. ICLR 2025LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
250. ICLR 2025LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning

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.