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

174 papers, page 2 of 4

51. NeurIPS 2025Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size
52. NeurIPS 2025Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation
53. NeurIPS 2025EquiTabPFN: A Target-Permutation Equivariant Prior Fitted Network
54. NeurIPS 2025Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models
55. NeurIPS 2025F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
56. NeurIPS 2025FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic
57. NeurIPS 2025Fantastic Features and Where to Find Them: A Probing Method to combine Features from Multiple Foundation Models
58. NeurIPS 2025Fast and Fluent Diffusion Language Models via Convolutional Decoding and Rejective Fine-tuning
59. NeurIPS 2025Fin3R: Fine-tuning Feed-forward 3D Reconstruction Models via Monocular Knowledge Distillation
60. NeurIPS 2025FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models
61. NeurIPS 2025FlyLoRA: Boosting Task Decoupling and Parameter Efficiency via Implicit Rank-Wise Mixture-of-Experts
62. NeurIPS 2025Fourier Analysis Network
63. NeurIPS 2025From Pretraining to Pathology: How Noise Leads to Catastrophic Inheritance in Medical Models
64. NeurIPS 2025Gains: Fine-grained Federated Domain Adaptation in Open Set
65. NeurIPS 2025GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation
66. NeurIPS 2025Gated Integration of Low-Rank Adaptation for Continual Learning of Large Language Models
67. NeurIPS 2025Generating Informative Samples for Risk-Averse Fine-Tuning of Downstream Tasks
68. NeurIPS 2025GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters
69. NeurIPS 2025GeoLink: Empowering Remote Sensing Foundation Model with OpenStreetMap Data
70. NeurIPS 2025Geometry-Aware Collaborative Multi-Solutions Optimizer for Model Fine-Tuning with Parameter Efficiency
71. NeurIPS 2025GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation
72. NeurIPS 2025GoRA: Gradient-driven Adaptive Low Rank Adaptation
73. NeurIPS 2025GraLoRA: Granular Low-Rank Adaptation for Parameter-Efficient Fine-Tuning
74. NeurIPS 2025GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning
75. NeurIPS 2025Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning
76. NeurIPS 2025Hyperbolic Fine-Tuning for Large Language Models
77. NeurIPS 2025Implicit Modeling for Transferability Estimation of Vision Foundation Models
78. NeurIPS 2025Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
79. NeurIPS 2025In-Context Learning of Stochastic Differential Equations with Foundation Inference Models
80. NeurIPS 2025Investigating Hallucinations of Time Series Foundation Models through Signal Subspace Analysis
81. NeurIPS 2025Iterative Foundation Model Fine-Tuning on Multiple Rewards
82. NeurIPS 2025JanusDNA: A Powerful Bi-directional Hybrid DNA Foundation Model
83. NeurIPS 2025Language Models Can Predict Their Own Behavior
84. NeurIPS 2025Latent Space Factorization in LoRA
85. NeurIPS 2025LaX: Boosting Low-Rank Training of Foundation Models via Latent Crossing
86. NeurIPS 2025Learning Source-Free Domain Adaptation for Visible-Infrared Person Re-Identification
87. NeurIPS 2025Learning to Factorize Spatio-Temporal Foundation Models
88. NeurIPS 2025Learning to Think: Information-Theoretic Reinforcement Fine-Tuning for LLMs
89. NeurIPS 2025Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning
90. NeurIPS 2025Linearization Explains Fine-Tuning in Large Language Models
91. NeurIPS 2025Loquetier: A Virtualized Multi-LoRA Framework for Unified LLM Fine-tuning and Serving
92. NeurIPS 2025LoRA vs Full Fine-tuning: An Illusion of Equivalence
93. NeurIPS 2025LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades
94. NeurIPS 2025LoTA-QAF: Lossless Ternary Adaptation for Quantization-Aware Fine-Tuning
95. NeurIPS 2025LT-Soups: Bridging Head and Tail Classes via Subsampled Model Soups
96. NeurIPS 2025LUNA: Efficient and Topology-Agnostic Foundation Model for EEG Signal Analysis
97. NeurIPS 2025Magical: Medical Lay Language Generation via Semantic Invariance and Layperson-tailored Adaptation
98. NeurIPS 2025MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants
99. NeurIPS 2025Metis: A Foundation Speech Generation Model with Masked Generative Pre-training
100. NeurIPS 2025MimeQA: Towards Socially-Intelligent Nonverbal Foundation Models

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.