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

270 papers, page 2 of 6

51. CVPR 2024Stronger Fewer & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation
52. CVPR 2024Time- Memory- and Parameter-Efficient Visual Adaptation
53. CVPR 2024Tuning Stable Rank Shrinkage: Aiming at the Overlooked Structural Risk in Fine-tuning
54. CVPR 2024Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias
55. CVPR 2024Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding
56. CVPR 2024Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning
57. ICLR 2024A Foundation Model for Error Correction Codes
58. ICLR 2024A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
59. ICLR 2024Adapting to Distribution Shift by Visual Domain Prompt Generation
60. ICLR 2024Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness
61. ICLR 2024An Emulator for Fine-tuning Large Language Models using Small Language Models
62. ICLR 2024AutoLoRa: An Automated Robust Fine-Tuning Framework
63. ICLR 2024AutoVP: An Automated Visual Prompting Framework and Benchmark
64. ICLR 2024Batched Low-Rank Adaptation of Foundation Models
65. ICLR 2024Bayesian Low-rank Adaptation for Large Language Models
66. ICLR 2024BrainLM: A foundation model for brain activity recordings
67. ICLR 2024C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion
68. ICLR 2024CLAP: Collaborative Adaptation for Patchwork Learning
69. ICLR 2024Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
70. ICLR 2024DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
71. ICLR 2024Differentially Private Synthetic Data via Foundation Model APIs 1: Images
72. ICLR 2024Directly Fine-Tuning Diffusion Models on Differentiable Rewards
73. ICLR 2024Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI
74. ICLR 2024Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs
75. ICLR 2024Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation
76. ICLR 2024Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors
77. ICLR 2024Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow
78. ICLR 2024Fast Imitation via Behavior Foundation Models
79. ICLR 2024Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
80. ICLR 2024Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking
81. ICLR 2024Fine-Tuning Language Models for Factuality
82. ICLR 2024Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs
83. ICLR 2024Gradual Domain Adaptation via Gradient Flow
84. ICLR 2024Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
85. ICLR 2024Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks
86. ICLR 2024Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation
87. ICLR 2024Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation
88. ICLR 2024Neural Fine-Tuning Search for Few-Shot Learning
89. ICLR 2024OVOR: OnePrompt with Virtual Outlier Regularization for Rehearsal-Free Class-Incremental Learning
90. ICLR 2024Pre-Training and Fine-Tuning Generative Flow Networks
91. ICLR 2024Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
92. ICLR 2024Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features
93. ICLR 2024QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
94. ICLR 2024Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
95. ICLR 2024The False Promise of Imitating Proprietary Language Models
96. ICLR 2024Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning
97. ICLR 2024Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation
98. ICLR 2024Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation
99. ICLR 2024Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition
100. ICLR 2024Two-stage LLM Fine-tuning with Less Specialization and More Generalization

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.