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 9 of 13

401. ICML 2026TarGATE: Target-Aware Data Selection via Token-Attenuation Gates
402. ICML 2026The Geometry of Narrow Fine-Tuning Degradation: Trajectory Lock-in and Spectral Bifurcation
403. ICML 2026The Geometry of Sequential Learning: Lie-Bracket Prediction of Transfer Order
404. ICML 2026Time-PEFT: Temporal and Multichannel Complexity-Based Fine-Tuning for Time-Series Foundation Models
405. ICML 2026Towards Fine-Grained Robustness: Attention-Guided Test-Time Prompt Tuning for Vision-Language Models
406. ICML 2026Towards Understanding the Dynamics of Low-Rank Adaptation
407. ICML 2026Trust It or Not: Evidential Uncertainty for Feed-Forward 3D Reconstruction with Trust3R
408. ICML 2026TuneAhead: Predicting Fine-tuning Performance Before Training Begins
409. ICML 2026UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models
410. ICML 2026Uncovering the Latent Potential of Deep Intermediate Representations
411. ICML 2026Universal Redundancies in Time Series Foundation Models
412. ICML 2026Unveiling Prior-Data Fitted Networks on Causal Effect Estimation: Pre-Training or Fine-Tuning?
413. ICML 2026Utility-Diversity Aware Online Batch Selection for LLM Supervised Fine-tuning
414. ICML 2026Walrus: A Cross-domain Foundation Model for Continuum Dynamics
415. ICML 2026Weight Updates as Activation Shifts: A Principled Framework for Steering
416. ICML 2026When Do Graph Foundation Models Transfer? A Data-Centric Theory
417. ICML 2026When More Data Doesn't Help: Limits of Adaptation in Multitask Learning
418. ICML 2026When Tabular Foundation Models Meet Strategic Tabular Data: A Prior Alignment Approach
419. ICML 2026WorldMirror: Universal 3D World Reconstruction with Any-Prior Prompting
420. ICML 2026Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis
421. NeurIPS 2026(Mis)generalization of Helpful-Only Fine-Tuning
422. NeurIPS 20263R-Adapter: Retrieval, Rewiring, and Refinement for Efficient Adaptation of 3D Reconstruction Model
423. NeurIPS 2026A Graph Foundation Model for Unified Clustering
424. NeurIPS 2026A low-rank decoder bottleneck bounds reliability in foundation-model perturbation prediction
425. NeurIPS 2026A unified pairwise distribution matching framework for graph domain adaptation under structure shift
426. NeurIPS 2026ABHBench: Evaluating Moral Decision-Making of Foundation Models from an Agentic Perspective
427. NeurIPS 2026AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation
428. NeurIPS 2026Aligned LoRA Updates via Intrinsic Geometry for Federated Low-Rank Adaptation
429. NeurIPS 2026Aligning LLMs with Biomedical Knowledge using Balanced Fine-Tuning
430. NeurIPS 2026Alignment Dynamics in LLM Fine-Tuning
431. NeurIPS 2026AmbientFM: A Foundation Model for Ambient Sensing
432. NeurIPS 2026An Analytical Model of Compute-limited Multistage Training Pipelines
433. NeurIPS 2026An Open-Source Training Dataset for Foundation Models for Black-box Optimization
434. NeurIPS 2026AR1-ZO: Topology-Aware Rank-1 Zeroth-Order Queries for High-Rank LoRA Fine-Tuning
435. NeurIPS 2026Auditing Privacy Leakage in Tabular Foundation Model Embeddings
436. NeurIPS 2026B[FM]$^2$: Brain Foundation Model via Flow Matching with SplitUNet
437. NeurIPS 2026Barycentric Guidance: Turning Foundation Image Editors into Continuous Affective Controllers
438. NeurIPS 2026Behavioral Foundation Models for Quality Diversity
439. NeurIPS 2026Behavioral Geometric Supervision Aligns Video Foundation Models with Human Social Perception
440. NeurIPS 2026Benchmarking Fine-Grained Spatio-Temporal Awareness in Embodied Brain Models
441. NeurIPS 2026Beyond IID: How General Are Tabular Foundation Models, Really?
442. NeurIPS 2026Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation
443. NeurIPS 2026Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction
444. NeurIPS 2026BQ-LoRA: Binary-Quantized Low-Rank Adapters as Implicit Regularizers for Parameter-Efficient Fine-Tuning
445. NeurIPS 2026C2FT: Enhancing Fine-Grained Perception in MLLMs via Confuse-then-Contrast Fine-Tuning
446. NeurIPS 2026Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention
447. NeurIPS 2026CanViT: Toward Active-Vision Foundation Models
448. NeurIPS 2026Certification-Enhanced Generalization Bounds
449. NeurIPS 2026ChildPose: Foundation for Children Pose Modeling
450. NeurIPS 2026CLEF: EEG Foundation Models for Learning Clinical Semantics

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.