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

192 papers, page 1 of 4

1. NeurIPS 2024$\textit{Read-ME}$: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design
2. NeurIPS 2024$C^2M^3$: Cycle-Consistent Multi-Model Merging
3. NeurIPS 20243-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability
4. NeurIPS 2024A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings
5. NeurIPS 2024A Walsh Hadamard Derived Linear Vector Symbolic Architecture
6. NeurIPS 2024Accelerating Transformers with Spectrum-Preserving Token Merging
7. NeurIPS 2024Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting
8. NeurIPS 2024AdanCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer
9. NeurIPS 2024Adaptive Depth Networks with Skippable Sub-Paths
10. NeurIPS 2024Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment
11. NeurIPS 2024Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning
12. NeurIPS 2024Algebraic Positional Encodings
13. NeurIPS 2024Alias-Free Mamba Neural Operator
14. NeurIPS 2024AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models
15. NeurIPS 2024Amortized Eigendecomposition for Neural Networks
16. NeurIPS 2024Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient
17. NeurIPS 2024Are Self-Attentions Effective for Time Series Forecasting?
18. NeurIPS 2024Asynchronous Perception Machine for Efficient Test Time Training
19. NeurIPS 2024AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
20. NeurIPS 2024B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory
21. NeurIPS 2024BOLD: Boolean Logic Deep Learning
22. NeurIPS 2024Breaking Long-Tailed Learning Bottlenecks: A Controllable Paradigm with Hypernetwork-Generated Diverse Experts
23. NeurIPS 2024Bridging the Divide: Reconsidering Softmax and Linear Attention
24. NeurIPS 2024Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation
25. NeurIPS 2024Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers
26. NeurIPS 2024CALANet: Cheap All-Layer Aggregation for Human Activity Recognition
27. NeurIPS 2024Calibrated Self-Rewarding Vision Language Models
28. NeurIPS 2024Can neural operators always be continuously discretized?
29. NeurIPS 2024CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework
30. NeurIPS 2024Cell ontology guided transcriptome foundation model
31. NeurIPS 2024Cherry on Top: Parameter Heterogeneity and Quantization in Large Language Models
32. NeurIPS 2024Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models
33. NeurIPS 2024Cluster-Learngene: Inheriting Adaptive Clusters for Vision Transformers
34. NeurIPS 2024CODA: A Correlation-Oriented Disentanglement and Augmentation Modeling Scheme for Better Resisting Subpopulation Shifts
35. NeurIPS 2024Compressing Large Language Models using Low Rank and Low Precision Decomposition
36. NeurIPS 2024CondTSF: One-line Plugin of Dataset Condensation for Time Series Forecasting
37. NeurIPS 2024ContactField: Implicit Field Representation for Multi-Person Interaction Geometry
38. NeurIPS 2024ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence
39. NeurIPS 2024CosAE: Learnable Fourier Series for Image Restoration
40. NeurIPS 2024Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning
41. NeurIPS 2024Coupled Mamba: Enhanced Multimodal Fusion with Coupled State Space Model
42. NeurIPS 2024CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object Detection
43. NeurIPS 2024D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup
44. NeurIPS 2024D2R2: Diffusion-based Representation with Random Distance Matching for Tabular Few-shot Learning
45. NeurIPS 2024DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution
46. NeurIPS 2024DeltaDEQ: Exploiting Heterogeneous Convergence for Accelerating Deep Equilibrium Iterations
47. NeurIPS 2024Demystify Mamba in Vision: A Linear Attention Perspective
48. NeurIPS 2024Dendritic Integration Inspired Artificial Neural Networks Capture Data Correlation
49. NeurIPS 2024Dense Associative Memory Through the Lens of Random Features
50. NeurIPS 2024DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging

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.