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 3 of 4

101. NeurIPS 2024MatFormer: Nested Transformer for Elastic Inference
102. NeurIPS 2024MatrixNet: Learning over symmetry groups using learned group representations
103. NeurIPS 2024Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
104. NeurIPS 2024MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers
105. NeurIPS 2024MeshXL: Neural Coordinate Field for Generative 3D Foundation Models
106. NeurIPS 2024Meta-Learning Universal Priors Using Non-Injective Change of Variables
107. NeurIPS 2024MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map
108. NeurIPS 2024Mixtures of Experts for Audio-Visual Learning
109. NeurIPS 2024MoEUT: Mixture-of-Experts Universal Transformers
110. NeurIPS 2024MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
111. NeurIPS 2024Monomial Matrix Group Equivariant Neural Functional Networks
112. NeurIPS 2024MoVA: Adapting Mixture of Vision Experts to Multimodal Context
113. NeurIPS 2024Multi-Head Mixture-of-Experts
114. NeurIPS 2024Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times
115. NeurIPS 2024Neural Experts: Mixture of Experts for Implicit Neural Representations
116. NeurIPS 2024NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
117. NeurIPS 2024On Feature Learning in Structured State Space Models
118. NeurIPS 2024On Sampling Strategies for Spectral Model Sharding
119. NeurIPS 2024Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling
120. NeurIPS 2024Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation
121. NeurIPS 2024Parallelizing Linear Transformers with the Delta Rule over Sequence Length
122. NeurIPS 2024Pedestrian-Centric 3D Pre-collision Pose and Shape Estimation from Dashcam Perspective
123. NeurIPS 2024Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers
124. NeurIPS 2024Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis
125. NeurIPS 2024PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting
126. NeurIPS 2024PointMamba: A Simple State Space Model for Point Cloud Analysis
127. NeurIPS 2024Poseidon: Efficient Foundation Models for PDEs
128. NeurIPS 2024PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond
129. NeurIPS 2024Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization
130. NeurIPS 2024ProxyFusion: Face Feature Aggregation Through Sparse Experts
131. NeurIPS 2024Q-VLM: Post-training Quantization for Large Vision-Language Models
132. NeurIPS 2024QT-ViT: Improving Linear Attention in ViT with Quadratic Taylor Expansion
133. NeurIPS 2024QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space Model
134. NeurIPS 2024QUEST: Quadruple Multimodal Contrastive Learning with Constraints and Self-Penalization
135. NeurIPS 2024Real-time Core-Periphery Guided ViT with Smart Data Layout Selection on Mobile Devices
136. NeurIPS 2024Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
137. NeurIPS 2024Reinforced Cross-Domain Knowledge Distillation on Time Series Data
138. NeurIPS 2024Relating Hopfield Networks to Episodic Control
139. NeurIPS 2024Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling
140. NeurIPS 2024Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints
141. NeurIPS 2024Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting
142. NeurIPS 2024Rethinking Imbalance in Image Super-Resolution for Efficient Inference
143. NeurIPS 2024Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models
144. NeurIPS 2024Retrieval & Fine-Tuning for In-Context Tabular Models
145. NeurIPS 2024Revisiting motion information for RGB-Event tracking with MOT philosophy
146. NeurIPS 2024Revisiting the Integration of Convolution and Attention for Vision Backbone
147. NeurIPS 2024RMLR: Extending Multinomial Logistic Regression into General Geometries
148. NeurIPS 2024Robustly overfitting latents for flexible neural image compression
149. NeurIPS 2024Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching
150. NeurIPS 2024Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD Prompts

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.