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

299 papers, page 4 of 6

151. NeurIPS 2024MoEUT: Mixture-of-Experts Universal Transformers
152. NeurIPS 2024MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
153. NeurIPS 2024Monomial Matrix Group Equivariant Neural Functional Networks
154. NeurIPS 2024MoVA: Adapting Mixture of Vision Experts to Multimodal Context
155. NeurIPS 2024Multi-Head Mixture-of-Experts
156. NeurIPS 2024Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times
157. NeurIPS 2024Neural Experts: Mixture of Experts for Implicit Neural Representations
158. NeurIPS 2024NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
159. NeurIPS 2024On Feature Learning in Structured State Space Models
160. NeurIPS 2024On Sampling Strategies for Spectral Model Sharding
161. NeurIPS 2024Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling
162. NeurIPS 2024Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation
163. NeurIPS 2024Parallelizing Linear Transformers with the Delta Rule over Sequence Length
164. NeurIPS 2024Pedestrian-Centric 3D Pre-collision Pose and Shape Estimation from Dashcam Perspective
165. NeurIPS 2024Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers
166. NeurIPS 2024Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis
167. NeurIPS 2024PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting
168. NeurIPS 2024PointMamba: A Simple State Space Model for Point Cloud Analysis
169. NeurIPS 2024Poseidon: Efficient Foundation Models for PDEs
170. NeurIPS 2024PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond
171. NeurIPS 2024Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization
172. NeurIPS 2024ProxyFusion: Face Feature Aggregation Through Sparse Experts
173. NeurIPS 2024Q-VLM: Post-training Quantization for Large Vision-Language Models
174. NeurIPS 2024QT-ViT: Improving Linear Attention in ViT with Quadratic Taylor Expansion
175. NeurIPS 2024QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space Model
176. NeurIPS 2024QUEST: Quadruple Multimodal Contrastive Learning with Constraints and Self-Penalization
177. NeurIPS 2024Real-time Core-Periphery Guided ViT with Smart Data Layout Selection on Mobile Devices
178. NeurIPS 2024Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
179. NeurIPS 2024Reinforced Cross-Domain Knowledge Distillation on Time Series Data
180. NeurIPS 2024Relating Hopfield Networks to Episodic Control
181. NeurIPS 2024Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling
182. NeurIPS 2024Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints
183. NeurIPS 2024Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting
184. NeurIPS 2024Rethinking Imbalance in Image Super-Resolution for Efficient Inference
185. NeurIPS 2024Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models
186. NeurIPS 2024Retrieval & Fine-Tuning for In-Context Tabular Models
187. NeurIPS 2024Revisiting motion information for RGB-Event tracking with MOT philosophy
188. NeurIPS 2024Revisiting the Integration of Convolution and Attention for Vision Backbone
189. NeurIPS 2024RMLR: Extending Multinomial Logistic Regression into General Geometries
190. NeurIPS 2024Robustly overfitting latents for flexible neural image compression
191. NeurIPS 2024Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching
192. NeurIPS 2024Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD Prompts
193. NeurIPS 2024S2HPruner: Soft-to-Hard Distillation Bridges the Discretization Gap in Pruning
194. NeurIPS 2024Scaling Law for Time Series Forecasting
195. NeurIPS 2024Scaling White-Box Transformers for Vision
196. NeurIPS 2024Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
197. NeurIPS 2024Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations
198. NeurIPS 2024Selective Attention: Enhancing Transformer through Principled Context Control
199. NeurIPS 2024Separations in the Representational Capabilities of Transformers and Recurrent Architectures
200. NeurIPS 2024Set-based Neural Network Encoding Without Weight Tying

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.