Deep learning · foundation models papers, 2023–2026

Key findings

• Deep learning · foundation models went from 72 papers in 2023 to 177 in 2026, roughly 2.5x in three years.
• NeurIPS publishes the most Deep learning · foundation models work: 299 papers from 2023 to 2026, 56% of the four-venue total.
• The fastest-growing overlap is with Foundation Model Adaptation: papers tagged with both rose from 7 in 2023 to 66 in 2026.
• Among the 11 topics under Deep Learning, it ranks #8 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 2.5x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Inferotemporal Cortex Collaborates Before It Codes: Non-Serial Inter-Area Synergy in the Macaque Ventral Stream
• ICML 2026ACO-MoE-LoRA: Evolving-while-Training for Adapting Segment Anything Model 2 to Specialized Domains
• ICLR 2026Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization
• CVPR 2026Adapting a Pre-trained Single-Cell Foundation Model to Spatial Gene Expression
• NeurIPS 2025An Investigation of Memorization Risk in Healthcare Foundation Models
• ICML 2025Contrastive Localized Language-Image Pre-Training
• ICLR 2025Revisiting Convolution Architecture in the Realm of DNA Foundation Models
• CVPR 2025DEFOM-Stereo: Depth Foundation Model Based Stereo Matching
• NeurIPS 2024$\textit{Read-ME}$: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design
• ICML 2024Position: On the Societal Impact of Open Foundation Models
• CVPR 20243D-LFM: Lifting Foundation Model
• NeurIPS 2023Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
• ICML 2023Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models
• NeurIPS 2026Do Pathology Foundation Models Encode Disease Progression? A Pseudotime Analysis of Visual Representations
• ICML 2026Alethia: a Foundational Encoder for Voice Deepfakes
• ICLR 2026DND: Boosting Large Language Models with Dynamic Nested Depth
• CVPR 2026UniSER A Foundation Model for Unified Soft Effects Removal
• NeurIPS 2025ChromFound: Towards A Universal Foundation Model for Single-Cell Chromatin Accessibiltiy Data
• ICML 2025Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
• ICLR 2025Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon

All Deep learning · foundation models papers

72 papers, page 1 of 2

1. ICML 2023$\pi$-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation
2. ICML 2023A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models
3. ICML 2023CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks
4. ICML 2023Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models
5. ICML 2023Learning Unnormalized Statistical Models via Compositional Optimization
6. ICML 2023Magneto: A Foundation Transformer
7. ICML 2023On the Power of Foundation Models
8. NeurIPS 20234M: Massively Multimodal Masked Modeling
9. NeurIPS 2023A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints
10. NeurIPS 2023ADGym: Design Choices for Deep Anomaly Detection
11. NeurIPS 2023Agnostically Learning Single-Index Models using Omnipredictors
12. NeurIPS 2023An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions
13. NeurIPS 2023BayesTune: Bayesian Sparse Deep Model Fine-tuning
14. NeurIPS 2023Beyond Confidence: Reliable Models Should Also Consider Atypicality
15. NeurIPS 2023BiMatting: Efficient Video Matting via Binarization
16. NeurIPS 2023Birth of a Transformer: A Memory Viewpoint
17. NeurIPS 2023Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
18. NeurIPS 2023C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models
19. NeurIPS 2023CHAMMI: A benchmark for channel-adaptive models in microscopy imaging
20. NeurIPS 2023Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task
21. NeurIPS 2023Contextually Affinitive Neighborhood Refinery for Deep Clustering
22. NeurIPS 2023Differentiable Random Partition Models
23. NeurIPS 2023Distributed Inference and Fine-tuning of Large Language Models Over The Internet
24. NeurIPS 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
25. NeurIPS 2023Efficient Equivariant Transfer Learning from Pretrained Models
26. NeurIPS 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
27. NeurIPS 2023Energy Transformer
28. NeurIPS 2023Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance
29. NeurIPS 2023Evaluating Neuron Interpretation Methods of NLP Models
30. NeurIPS 2023Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
31. NeurIPS 2023Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models
32. NeurIPS 2023Foundation Model is Efficient Multimodal Multitask Model Selector
33. NeurIPS 2023FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models
34. NeurIPS 2023Generalized Logit Adjustment: Calibrating Fine-tuned Models by Removing Label Bias in Foundation Models
35. NeurIPS 2023Generating QM1B with PySCF$_{\text{IPU}}$
36. NeurIPS 2023GEO-Bench: Toward Foundation Models for Earth Monitoring
37. NeurIPS 2023Geometry-Aware Adaptation for Pretrained Models
38. NeurIPS 2023Global Optimality in Bivariate Gradient-based DAG Learning
39. NeurIPS 2023Grassmann Manifold Flows for Stable Shape Generation
40. NeurIPS 2023Guiding The Last Layer in Federated Learning with Pre-Trained Models
41. NeurIPS 2023Large Language Models can Implement Policy Iteration
42. NeurIPS 2023Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition
43. NeurIPS 2023Learning Sample Difficulty from Pre-trained Models for Reliable Prediction
44. NeurIPS 2023LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition
45. NeurIPS 2023Module-wise Adaptive Distillation for Multimodality Foundation Models
46. NeurIPS 2023Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine
47. NeurIPS 2023Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes
48. NeurIPS 2023On Learning Latent Models with Multi-Instance Weak Supervision
49. NeurIPS 2023Paxion: Patching Action Knowledge in Video-Language Foundation Models
50. NeurIPS 2023Quantification of Uncertainty with Adversarial Models

FAQ

How many Deep learning · foundation models papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

536 in total: 72 in 2023, 209 in 2024, 78 in 2025, 177 in 2026.

How many Deep learning · foundation models papers are at NeurIPS 2026?

NeurIPS 2026 has 27 Deep learning · foundation models papers, versus 15 the year before.

How many Deep learning · foundation models papers are at ICLR 2026?

ICLR 2026 has 8 Deep learning · foundation models papers, versus 6 the year before.

How many Deep learning · foundation models papers are at ICML 2026?

ICML 2026 has 135 Deep learning · foundation models papers, versus 53 the year before.

How many Deep learning · foundation models papers are at CVPR 2026?

CVPR 2026 has 7 Deep learning · foundation models papers, versus 4 the year before.

Which conference publishes the most Deep learning · foundation models papers?

NeurIPS, with 299 papers from 2023 to 2026.