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 12 of 13

551. NeurIPS 2026RAHF: Reward-Amplified Human Feedback for Closed-Loop Policy Fine-Tuning
552. NeurIPS 2026Raw-Routed Mixture of Adapters: A Causal Intervention for Routing Collapse in Time Series Foundation Models
553. NeurIPS 2026RayTun3R: Online Camera Adaptation in 3D Foundation Models
554. NeurIPS 2026Reasoning-Trace Collapse: Evaluating the Loss of Explicit Reasoning During Fine-Tuning
555. NeurIPS 2026Relation-Aware Graph Foundation Model
556. NeurIPS 2026Resource-Aware Parameter-Efficient Model Adaptation for Onboard High-Dimensional Data
557. NeurIPS 2026Rest-Tuning: Data-Efficient Adaptation of EEG Foundation Models to Individuals via Resting-State Signals
558. NeurIPS 2026Rethinking "RL Generalizes, SFT Memorizes": The Role of SFT Data
559. NeurIPS 2026Rethinking LLM Fine-Tuning via Weight Space Reparameterization: Preserving Safety during Downstream Adaptation
560. NeurIPS 2026RIZZ: Routing Interactions to Near Zero-Interference Zones for Continual Adaptation of Black-Box Agents
561. NeurIPS 2026Robust and Efficient Finetuning of Vision Foundation Models via Implicit Ensembling
562. NeurIPS 2026Robust Diffusion Models via Divergence-Induced Weighted Denoising
563. NeurIPS 2026SaMA: Morpho Adaptation via Asymmetric Expansion of Kronecker Product
564. NeurIPS 2026SapiensID 2.0: Aligning Human Recognition Foundation Models with Human Perception
565. NeurIPS 2026Scalable Adaptation of 3D Geometric Foundation Models via Weak Supervision from Internet Video
566. NeurIPS 2026Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters
567. NeurIPS 2026ScreenShot: A Foundation Model for Few-Shot Combination Drug Screening
568. NeurIPS 2026SDS-LoRA: Overcoming Anisotropic Gradient Scaling in Low-Rank Adaptation
569. NeurIPS 2026SLDR: Defending Against Malicious Fine-tuning via Selective Layers Recovery and Dynamic Routing
570. NeurIPS 2026Solver-as-Teacher: Solver-Guided On-Policy Post-Training Framework for PDE Foundation Models
571. NeurIPS 2026SPIRIT: Speed-Driven Online Adaptation for Self-Speculative Decoding
572. NeurIPS 2026Stability Regimes for Framing-Sensitive Fine-Tuning in Language Models
573. NeurIPS 2026Tabular Foundation Model for Generative Modelling
574. NeurIPS 2026TACO: Towards Task-Consistent Open-Vocabulary Adaptation in Video Recognition
575. NeurIPS 2026Tadpole: Autoencoders as Foundation Models for 3D PDEs with Online Learning
576. NeurIPS 2026The Geometry of Alignment Collapse: When Fine-Tuning Breaks Safety
577. NeurIPS 2026The Optimal Control Foundation of Early Exits – Turnpikes and ResNets
578. NeurIPS 2026The Surprising Effectiveness of Deleting Weights in LLM Reasoning and Adaptation
579. NeurIPS 2026Towards Identifying Dominant Low-Rank Subspaces in Zeroth-Order Fine-Tuning
580. NeurIPS 2026Towards Reconstructing Geographically Diverse Architecture with 3D Foundation Models
581. NeurIPS 2026Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning
582. NeurIPS 2026Trust the Direction, Search the Step: Zero-and-First-Order Methods for LLM Fine-Tuning
583. NeurIPS 2026TS-ICL: A Flexible Time-Indexed Foundation Model for Time Series via In-Context Learning
584. NeurIPS 2026Tune-Up Open-Weight CLIP: Optimization Framework for Self-Supervised Fine-tuning of CLIP
585. NeurIPS 2026Tuning the Tuner
586. NeurIPS 2026U-MOF: Uncertainty-Guided Parameter-Efficient Multi-Objective Fine-Tuning for Long-Tailed Recognition
587. NeurIPS 2026Uncertainty-Aware Listwise Reinforcement Fine-Tuning for Fine-Grained Visual Classification
588. NeurIPS 2026Unified Panoramic Geometry Estimation via Multi-View Foundation Models
589. NeurIPS 2026Unveiling Implicit Advantage Symmetry: Why GRPO Struggles with Exploration and Difficulty Adaptation
590. NeurIPS 2026Vibe-Spike: An Energy-Preserving EEG Foundation Model Through the Landscape of Neural Coherence
591. NeurIPS 2026What DNA Foundation Models Learn Beyond Sequence Composition
592. NeurIPS 2026What do EEG Foundation Models Capture from Human Brain Signals?
593. NeurIPS 2026What Does an Observability Forecasting Foundation Model Know?
594. NeurIPS 2026What Drives Test-Time Adaptation for CLIP? A Controlled Empirical Study from an Update Perspective
595. NeurIPS 2026When Catastrophic Inheritance Meets Forgetting in Continual Adaptation of Foundation Models
596. NeurIPS 2026When does LeJEPA learn a World Model?
597. NeurIPS 2026When the Merge Coefficient Stops Mattering: Proximity Regularized Merging for Continual LoRA Adaptation
598. NeurIPS 2026When to Trust a PFN: Detecting Harmful Shift in Tabular Foundation Models
599. NeurIPS 2026Where Do We (Not) Need Temporal Context in Low-Resource Video Task Adaptation?
600. NeurIPS 2026Where You Backpropagate Matters: Token Hypothesis for Memory-Efficient Fine-Tuning

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.