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

1,492 papers, page 17 of 30

801. ICLR 2025Towards Foundation Models for Mixed Integer Linear Programming
802. ICLR 2025Training-Free Activation Sparsity in Large Language Models
803. ICLR 2025Transformer-Squared: Self-adaptive LLMs
804. ICLR 2025Unleashing the Power of Task-Specific Directions in Parameter Efficient Fine-tuning
805. ICLR 2025Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning
806. ICLR 2025Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs
807. ICLR 2025VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation
808. ICLR 2025Weakly-Supervised Affordance Grounding Guided by Part-Level Semantic Priors
809. ICLR 2025When Attention Sink Emerges in Language Models: An Empirical View
810. ICLR 2025X-Fi: A Modality-Invariant Foundation Model for Multimodal Human Sensing
811. ICLR 2025Zero-shot Imputation with Foundation Inference Models for Dynamical Systems
812. ICLR 2025Zeroth-Order Fine-Tuning of LLMs with Transferable Static Sparsity
813. ICLR 2025ZooProbe: A Data Engine for Evaluating, Exploring, and Evolving Large-scale Training Data for Multimodal LLMs
814. ICML 2025A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
815. ICML 2025A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
816. ICML 2025Adapting to Evolving Adversaries with Regularized Continual Robust Training
817. ICML 2025AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
818. ICML 2025Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
819. ICML 2025Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety
820. ICML 2025Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions
821. ICML 2025Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
822. ICML 2025Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between Samples
823. ICML 2025Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers
824. ICML 2025Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation
825. ICML 2025Contextures: Representations from Contexts
826. ICML 2025Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
827. ICML 2025Efficient Personalized Adaptation for Physiological Signal Foundation Model
828. ICML 2025ELoRA: Low-Rank Adaptation for Equivariant GNNs
829. ICML 2025Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization
830. ICML 2025Enhancing Foundation Models with Federated Domain Knowledge Infusion
831. ICML 2025ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts
832. ICML 2025Fast and Low-Cost Genomic Foundation Models via Outlier Removal
833. ICML 2025Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
834. ICML 2025Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset Selection
835. ICML 2025From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control
836. ICML 2025GAPrompt: Geometry-Aware Point Cloud Prompt for 3D Vision Model
837. ICML 2025Griffin: Towards a Graph-Centric Relational Database Foundation Model
838. ICML 2025In-Context Adaptation to Concept Drift for Learned Database Operations
839. ICML 2025In-Context Fine-Tuning for Time-Series Foundation Models
840. ICML 2025InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective
841. ICML 2025Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning
842. ICML 2025L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning
843. ICML 2025Large Continual Instruction Assistant
844. ICML 2025Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning
845. ICML 2025Lightweight Online Adaption for Time Series Foundation Model Forecasts
846. ICML 2025LoRA Training Provably Converges to a Low-Rank Global Minimum Or It Fails Loudly (But it Probably Won't Fail)
847. ICML 2025MixMin: Finding Data Mixtures via Convex Minimization
848. ICML 2025Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
849. ICML 2025NextCoder: Robust Adaptation of Code LMs to Diverse Code Edits
850. ICML 2025OmniArch: Building Foundation Model for Scientific Computing

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.