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 6 of 9

251. ICLR 2025LoLCATs: On Low-Rank Linearizing of Large Language Models
252. ICLR 2025LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation
253. ICLR 2025LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
254. ICLR 2025LoRA-X: Bridging Foundation Models with Training-Free Cross-Model Adaptation
255. ICLR 2025LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation models
256. ICLR 2025Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction
257. ICLR 2025Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning
258. ICLR 2025MallowsPO: Fine-Tune Your LLM with Preference Dispersions
259. ICLR 2025MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba
260. ICLR 2025MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods
261. ICLR 2025Matryoshka Multimodal Models
262. ICLR 2025Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering
263. ICLR 2025MeteoRA: Multiple-tasks Embedded LoRA for Large Language Models
264. ICLR 2025Mitigating Memorization in Language Models
265. ICLR 2025Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment
266. ICLR 2025Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN
267. ICLR 2025MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning
268. ICLR 2025Model Equality Testing: Which Model is this API Serving?
269. ICLR 2025MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling
270. ICLR 2025Montessori-Instruct: Generate Influential Training Data Tailored for Student Learning
271. ICLR 2025MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture of Shards
272. ICLR 2025MTSAM: Multi-Task Fine-Tuning for Segment Anything Model
273. ICLR 2025Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning
274. ICLR 2025Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning
275. ICLR 2025Neural Phylogeny: Fine-Tuning Relationship Detection among Neural Networks
276. ICLR 2025nGPT: Normalized Transformer with Representation Learning on the Hypersphere
277. ICLR 2025NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals
278. ICLR 2025NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval
279. ICLR 2025On the Optimization Landscape of Low Rank Adaptation Methods for Large Language Models
280. ICLR 2025PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
281. ICLR 2025PEARL: Towards Permutation-Resilient LLMs
282. ICLR 2025PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches
283. ICLR 2025Preserving Diversity in Supervised Fine-Tuning of Large Language Models
284. ICLR 2025ProteinBench: A Holistic Evaluation of Protein Foundation Models
285. ICLR 2025Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning
286. ICLR 2025QERA: an Analytical Framework for Quantization Error Reconstruction
287. ICLR 2025Quantized Spike-driven Transformer
288. ICLR 2025Quantum-PEFT: Ultra parameter-efficient fine-tuning
289. ICLR 2025RaSA: Rank-Sharing Low-Rank Adaptation
290. ICLR 2025RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation
291. ICLR 2025Re-Imagining Multimodal Instruction Tuning: A Representation View
292. ICLR 2025RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks
293. ICLR 2025Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon
294. ICLR 2025Reconstructive Visual Instruction Tuning
295. ICLR 2025Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer
296. ICLR 2025Revisiting Convolution Architecture in the Realm of DNA Foundation Models
297. ICLR 2025Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts
298. ICLR 2025ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL
299. ICLR 2025RRM: Robust Reward Model Training Mitigates Reward Hacking
300. ICLR 2025SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation

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.