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

602 papers, page 8 of 13

351. ICML 2026Learning in the Fisher Subspace: A Guided Initialization for LoRA Fine-Tuning
352. ICML 2026LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models
353. ICML 2026Low Kruskal-Rank Adaptation
354. ICML 2026LOZO+: Provably Efficient Zeroth-Order Fine-Tuning via Greedy Low-Rank Subspace Selection
355. ICML 2026Mantis: Lightweight Foundation Model for Time Series Classification
356. ICML 2026MDGMIX: Boundary-Aware Subgraph Mixing for Multi-Domain Graph Pre-Training
357. ICML 2026Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective
358. ICML 2026MetaPerch: Learning from metadata for bioacoustics foundation models
359. ICML 2026Midtraining Bridges Pretraining and Posttraining Distributions
360. ICML 2026MODEL SOUPS NEED ONLY ONE INGREDIENT
361. ICML 2026Multi-Label Test-Time Adaptation with Bayesian Conditional Priors
362. ICML 2026MultiLoReFT: Decoupling Shared and Modality-Specific Subspaces in Multimodal Learning via Low-Rank Representation Fine-Tuning
363. ICML 2026NeuroCLUS: A Foundation Model with Functional Clustering for Intracranial Neural Decoding
364. ICML 2026No Need to Train Your RDB Foundation Model
365. ICML 2026Olivia: Harmonizing Time Series Foundation Models with Power Spectral Density
366. ICML 2026Omni-fMRI: A Universal Atlas-Free fMRI Foundation Model
367. ICML 2026On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
368. ICML 2026Origo: Interpretable Multi-physics PDE Foundation Model through Neural Operator Splitting
369. ICML 2026PATCHCODE: Discrete Latent Predictive Learning for EEG Foundation Model
370. ICML 2026PFT: Phonon Fine-tuning for Machine Learned Interatomic Potentials
371. ICML 2026PISA: Privacy-Preserving Split Adaptation with Model IP Protection
372. ICML 2026PixCLIP: Towards Fine-grained Vision-Language Understanding via Any-granularity Pixel-Text Alignment
373. ICML 2026PLATE: Plasticity-Tunable Efficient Adapters for Geometry-Aware Continual Learning
374. ICML 2026PLoRA: Efficient Concurrent LoRA Training for Large Language Models
375. ICML 2026Preference Goal Tuning: Post-Training as Latent Control for Frozen Policies
376. ICML 2026Progressive Graph Structure Adjustment for Homophily Shift Adaptation
377. ICML 2026Quantifying the Uncertainty of Foundation Models with Singular Value Ensembles
378. ICML 2026Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting
379. ICML 2026Rethinking the Flow-based Gradual Domain Adaptation: A Semi-Dual Optimal Transport Perspective
380. ICML 2026SALAAD: Sparse And Low-Rank Adaptation via ADMM for Large Language Model Inference
381. ICML 2026Saving Foundation Flow-Matching Priors for Inverse Problems
382. ICML 2026Scaling Behavior in Model Fine-tuning for Audio DeepFake Detection
383. ICML 2026ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
384. ICML 2026scDEBART: Predicting in silico Single-Cell Perturbation Responses via Large-Scale Differential Expression Learning
385. ICML 2026See More, Forecast Better and Faster: Enhancing Time Series Foundation Models via Inference-Time Plug-and-Play Downsampling
386. ICML 2026SHERPA: Fine-tuning Segment Anything Models with Task-relevant Guidance
387. ICML 2026SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass
388. ICML 2026SleepMaMi: A Universal Sleep Foundation Model for Integrating Macro- and Micro-structures
389. ICML 2026SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
390. ICML 2026SpanNorm: Reconciling Training Stability and Performance in Deep Transformers
391. ICML 2026SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance–Diversity Data Selection
392. ICML 2026Spectral Imbalance Causes Forgetting in Low-Rank Continual Adaptation
393. ICML 2026SPR: A Structured Prompt Refinement Network for Modality Missing
394. ICML 2026StarEmbed: Benchmarking Time Series Foundation Models on Astronomical Observations of Variable Stars
395. ICML 2026Subgroup Discovery with the Cox Model
396. ICML 2026SURGE: Surrogate Gradient Adaptation in Binary Neural Networks
397. ICML 2026Surgery: Mitigating Harmful Fine-Tuning for Large Language Models via Attention Sink
398. ICML 2026TabICLv2: A Better, Faster, Scalable, and Open Tabular Foundation Model
399. ICML 2026TabMGP: Martingale Posterior with TabPFN
400. ICML 2026TabSwift: An Efficient Tabular Foundation Model with Row-Wise Attention

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.