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 8 of 9

351. ICLR 2024Differentially Private Synthetic Data via Foundation Model APIs 1: Images
352. ICLR 2024Directly Fine-Tuning Diffusion Models on Differentiable Rewards
353. ICLR 2024Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI
354. ICLR 2024Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs
355. ICLR 2024Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation
356. ICLR 2024Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors
357. ICLR 2024Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow
358. ICLR 2024Fast Imitation via Behavior Foundation Models
359. ICLR 2024Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
360. ICLR 2024Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking
361. ICLR 2024Fine-Tuning Language Models for Factuality
362. ICLR 2024Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs
363. ICLR 2024Gradual Domain Adaptation via Gradient Flow
364. ICLR 2024Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
365. ICLR 2024Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks
366. ICLR 2024Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation
367. ICLR 2024Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation
368. ICLR 2024Neural Fine-Tuning Search for Few-Shot Learning
369. ICLR 2024OVOR: OnePrompt with Virtual Outlier Regularization for Rehearsal-Free Class-Incremental Learning
370. ICLR 2024Pre-Training and Fine-Tuning Generative Flow Networks
371. ICLR 2024Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
372. ICLR 2024Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features
373. ICLR 2024QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
374. ICLR 2024Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
375. ICLR 2024The False Promise of Imitating Proprietary Language Models
376. ICLR 2024Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning
377. ICLR 2024Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation
378. ICLR 2024Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation
379. ICLR 2024Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition
380. ICLR 2024Two-stage LLM Fine-tuning with Less Specialization and More Generalization
381. ICLR 2024UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science
382. ICLR 2024VeRA: Vector-based Random Matrix Adaptation
383. ICLR 2024When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations
384. ICLR 2024WizardCoder: Empowering Code Large Language Models with Evol-Instruct
385. ICLR 2024WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions
386. ICLR 2024Zero-Shot Robustification of Zero-Shot Models
387. ICLR 2023A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias
388. ICLR 2023Consolidator: Mergable Adapter with Group Connections for Visual Adaptation
389. ICLR 2023Dirichlet-based Uncertainty Calibration for Active Domain Adaptation
390. ICLR 2023Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors
391. ICLR 2023Energy-Based Test Sample Adaptation for Domain Generalization
392. ICLR 2023ESD: Expected Squared Difference as a Tuning-Free Trainable Calibration Measure
393. ICLR 2023Graph Domain Adaptation via Theory-Grounded Spectral Regularization
394. ICLR 2023Hyper-Decision Transformer for Efficient Online Policy Adaptation
395. ICLR 2023Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation
396. ICLR 2023Lossless Adaptation of Pretrained Vision Models For Robotic Manipulation
397. ICLR 2023Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models
398. ICLR 2023Self-Distillation for Further Pre-training of Transformers
399. ICLR 2023Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
400. ICLR 2023The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning

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.