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

206 papers, page 4 of 5

151. ICML 2025GraphGPT: Generative Pre-trained Graph Eulerian Transformer
152. ICML 2025Griffin: Towards a Graph-Centric Relational Database Foundation Model
153. ICML 2025How Expressive are Knowledge Graph Foundation Models?
154. ICML 2025How Far Is Video Generation from World Model: A Physical Law Perspective
155. ICML 2025Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens
156. ICML 2025In-Context Deep Learning via Transformer Models
157. ICML 2025In-Context Learning as Conditioned Associative Memory Retrieval
158. ICML 2025Large Continual Instruction Assistant
159. ICML 2025Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning
160. ICML 2025Learning to (Learn at Test Time): RNNs with Expressive Hidden States
161. ICML 2025LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding
162. ICML 2025M+: Extending MemoryLLM with Scalable Long-Term Memory
163. ICML 2025Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization Alignment
164. ICML 2025MM-RLHF: The Next Step Forward in Multimodal LLM Alignment
165. ICML 2025MUDDFormer: Breaking Residual Bottlenecks in Transformers via Multiway Dynamic Dense Connections
166. ICML 2025On Path to Multimodal Generalist: General-Level and General-Bench
167. ICML 2025Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads
168. ICML 2025Peri-LN: Revisiting Normalization Layer in the Transformer Architecture
169. ICML 2025Physics-informed Temporal Alignment for Auto-regressive PDE Foundation Models
170. ICML 2025Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
171. ICML 2025Primitive Vision: Improving Diagram Understanding in MLLMs
172. ICML 2025QMamba: On First Exploration of Vision Mamba for Image Quality Assessment
173. ICML 2025Reasoning Limitations of Multimodal Large Language Models. A case study of Bongard Problems
174. ICML 2025Rethinking the Bias of Foundation Model under Long-tailed Distribution
175. ICML 2025Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection
176. ICML 2025Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation
177. ICML 2025SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
178. ICML 2025Sundial: A Family of Highly Capable Time Series Foundation Models
179. ICML 2025TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
180. ICML 2025The Double-Ellipsoid Geometry of CLIP
181. ICML 2025The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models Via Visual Information Steering
182. ICML 2025Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees
183. ICML 2025Towards Rationale-Answer Alignment of LVLMs via Self-Rationale Calibration
184. ICML 2025Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models
185. ICML 2025What Has a Foundation Model Found? Inductive Bias Reveals World Models
186. ICML 2025What If We Recaption Billions of Web Images with LLaMA-3?
187. ICML 2025Whitened CLIP as a Likelihood Surrogate of Images and Captions
188. ICML 2025WildChat-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
189. ICML 2024Asymmetry in Low-Rank Adapters of Foundation Models
190. ICML 2024Differentially Private Bias-Term Fine-tuning of Foundation Models
191. ICML 2024Foundation Policies with Hilbert Representations
192. ICML 2024Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
193. ICML 2024MOMENT: A Family of Open Time-series Foundation Models
194. ICML 2024Position: On the Societal Impact of Open Foundation Models
195. ICML 2024Position: Why Tabular Foundation Models Should Be a Research Priority
196. ICML 2024Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models
197. ICML 2024Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models
198. ICML 2024To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO
199. ICML 2024Transferring Knowledge From Large Foundation Models to Small Downstream Models
200. ICML 2023$\pi$-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation

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.