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 2 of 9

51. ICLR 2026Discrete Adjoint Matching
52. ICLR 2026Discrete Latent Features Ablate Adversarial Attack: A Robust Prompt Tuning Framework for VLMs
53. ICLR 2026Distilling to Hybrid Attention Models via KL-Guided Layer Selection
54. ICLR 2026DMAP: A Distribution Map for Text
55. ICLR 2026DND: Boosting Large Language Models with Dynamic Nested Depth
56. ICLR 2026E²LoRA: Efficient and Effective Low-Rank Adaptation with Entropy-Guided Adaptive Sharing
57. ICLR 2026Efficient Orthogonal Fine-Tuning with Principal Subspace Adaptation
58. ICLR 2026Embodied Navigation Foundation Model
59. ICLR 2026Enabling Fine-Tuning of Direct Feedback Alignment via Feedback-Weight Matching
60. ICLR 2026Escaping Policy Contraction: Contraction-Aware PPO (CaPPO) for Stable Language Model Fine-Tuning
61. ICLR 2026Explainable Token-level Noise Filtering for LLM Fine-tuning Datasets
62. ICLR 2026Exploring Interpretability for Visual Prompt Tuning with Cross-layer Concepts
63. ICLR 2026Exploring the Basin-Like Loss Landscape in Large Language Models
64. ICLR 2026Fine-Grained Activation Steering: Steering Less, Achieving More
65. ICLR 2026Fine-tuning Behavioral Cloning Policies with Preference‑Based Reinforcement Learning
66. ICLR 2026Fine-Tuning Diffusion Models via Intermediate Distribution Shaping
67. ICLR 2026Fine-tuning Done Right in Model Editing
68. ICLR 2026Fine-tuning Quantized Neural Networks with Zeroth-order Optimization
69. ICLR 2026FlexLoRA: Entropy-Guided Flexible Low-Rank Adaptation
70. ICLR 2026Flock: A Knowledge Graph Foundation Model via Learning on Random Walks
71. ICLR 2026FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment
72. ICLR 2026FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics
73. ICLR 2026FoNE: Precise Single-Token Number Embeddings via Fourier Features
74. ICLR 2026FZOO: Fast Zeroth-Order Optimizer for Fine‑Tuning Large Language Models towards Adam‑Scale Speed
75. ICLR 2026GIT-BO: High-Dimensional Bayesian Optimization with Tabular Foundation Models
76. ICLR 2026Gradient Intrinsic Dimensionality Alignment：Narrowing The Gap Between Low-Rank Adaptation and Full Fine-Tuning
77. ICLR 2026Gradient-Sign Masking for Task Vector Transport Across Pre-Trained Models
78. ICLR 2026GranViT: A Fine-Grained Vision Model With Autoregressive Perception For MLLMs
79. ICLR 2026Heterogeneous Federated Fine-Tuning with Parallel One-Rank Adaptation
80. ICLR 2026High Accuracy, Less Talk (HALT): Reliable LLMs through Capability-Aligned Finetuning
81. ICLR 2026Holdout-Loss-Based Data Selection for LLM Finetuning via In-Context Learning
82. ICLR 2026Homeostatic Adaptation of Optimal Population Codes under Metabolic Stress
83. ICLR 2026How Base Frequency Shapes RoPE: An Analytical Study of Frequency-Band Formation
84. ICLR 2026HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs
85. ICLR 2026IA2: Alignment with ICL Activations improves Supervised Fine-Tuning
86. ICLR 2026IDEAL: Data Equilibrium Adaptation for Multi-Capability Language Model Alignment
87. ICLR 2026IGU-LoRA: Adaptive Rank Allocation via Integrated Gradients and Uncertainty-Aware Scoring
88. ICLR 2026Improving Block-Wise LLM Quantization by 4-bit Block-Wise Optimal Float (BOF4): Analysis and Variations
89. ICLR 2026IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation
90. ICLR 2026In-Context Learning of Temporal Point Processes with Foundation Inference Models
91. ICLR 2026Is Finer Better? The Limits of Microscaling Formats in Large Language Models
92. ICLR 2026Joint Adaptation of Uni-modal Foundation Models for Multi-modal Alzheimer's Disease Diagnosis
93. ICLR 2026KeepLoRA: Continual Learning with Residual Gradient Adaptation
94. ICLR 2026Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions
95. ICLR 2026LinguaMap: Which Layers of LLMs Speak Your Language and How to Tune Them?
96. ICLR 2026LoFT: Low-Rank Adaptation That Behaves Like Full Fine-Tuning
97. ICLR 2026Log-Linear Attention
98. ICLR 2026Long-tailed Test-Time Adaptation for Vision-Language Models
99. ICLR 2026LoRA meets Riemannion: Muon Optimizer for Parametrization-independent Low-Rank Adapters
100. ICLR 2026LoRA-S: An Efficient Low Rank Adaptation scheme via Sylvester equation

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.