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

209 papers, page 3 of 5

101. NeurIPS 2024Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting
102. NeurIPS 2024Is Multiple Object Tracking a Matter of Specialization?
103. NeurIPS 2024Kraken: Inherently Parallel Transformers For Efficient Multi-Device Inference
104. NeurIPS 2024L-TTA: Lightweight Test-Time Adaptation Using a Versatile Stem Layer
105. NeurIPS 2024LaSCal: Label-Shift Calibration without target labels
106. NeurIPS 2024Latent Functional Maps: a spectral framework for representation alignment
107. NeurIPS 2024Learning diverse causally emergent representations from time series data
108. NeurIPS 2024Learning from Highly Sparse Spatio-temporal Data
109. NeurIPS 2024Learning Group Actions on Latent Representations
110. NeurIPS 2024Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees
111. NeurIPS 2024Learning symmetries via weight-sharing with doubly stochastic tensors
112. NeurIPS 2024Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios
113. NeurIPS 2024Linearly Decomposing and Recomposing Vision Transformers for Diverse-Scale Models
114. NeurIPS 2024LinNet: Linear Network for Efficient Point Cloud Representation Learning
115. NeurIPS 2024LLM-AutoDA: Large Language Model-Driven Automatic Data Augmentation for Long-tailed Problems
116. NeurIPS 2024MambaTree: Tree Topology is All You Need in State Space Model
117. NeurIPS 2024Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages
118. NeurIPS 2024MatFormer: Nested Transformer for Elastic Inference
119. NeurIPS 2024MatrixNet: Learning over symmetry groups using learned group representations
120. NeurIPS 2024Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
121. NeurIPS 2024MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers
122. NeurIPS 2024MeshXL: Neural Coordinate Field for Generative 3D Foundation Models
123. NeurIPS 2024Meta-Learning Universal Priors Using Non-Injective Change of Variables
124. NeurIPS 2024MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map
125. NeurIPS 2024Mixtures of Experts for Audio-Visual Learning
126. NeurIPS 2024MoEUT: Mixture-of-Experts Universal Transformers
127. NeurIPS 2024MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
128. NeurIPS 2024Monomial Matrix Group Equivariant Neural Functional Networks
129. NeurIPS 2024MoVA: Adapting Mixture of Vision Experts to Multimodal Context
130. NeurIPS 2024Multi-Head Mixture-of-Experts
131. NeurIPS 2024Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times
132. NeurIPS 2024Neural Experts: Mixture of Experts for Implicit Neural Representations
133. NeurIPS 2024NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
134. NeurIPS 2024On Feature Learning in Structured State Space Models
135. NeurIPS 2024On Sampling Strategies for Spectral Model Sharding
136. NeurIPS 2024Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling
137. NeurIPS 2024Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation
138. NeurIPS 2024Parallelizing Linear Transformers with the Delta Rule over Sequence Length
139. NeurIPS 2024Pedestrian-Centric 3D Pre-collision Pose and Shape Estimation from Dashcam Perspective
140. NeurIPS 2024Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers
141. NeurIPS 2024Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis
142. NeurIPS 2024PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting
143. NeurIPS 2024PointMamba: A Simple State Space Model for Point Cloud Analysis
144. NeurIPS 2024Poseidon: Efficient Foundation Models for PDEs
145. NeurIPS 2024PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond
146. NeurIPS 2024Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization
147. NeurIPS 2024ProxyFusion: Face Feature Aggregation Through Sparse Experts
148. NeurIPS 2024Q-VLM: Post-training Quantization for Large Vision-Language Models
149. NeurIPS 2024QT-ViT: Improving Linear Attention in ViT with Quadratic Taylor Expansion
150. NeurIPS 2024QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space Model

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.