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

536 papers, page 6 of 11

251. NeurIPS 2025Learning to Factorize Spatio-Temporal Foundation Models
252. NeurIPS 2025Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning
253. NeurIPS 2025Mitra: Mixed Synthetic Priors for Enhancing Tabular Foundation Models
254. NeurIPS 2025NeurIPT: Foundation Model for Neural Interfaces
255. NeurIPS 2025UniTraj: Learning a Universal Trajectory Foundation Model from Billion-Scale Worldwide Traces
256. CVPR 20243D-LFM: Lifting Foundation Model
257. CVPR 2024Asymmetric Masked Distillation for Pre-Training Small Foundation Models
258. CVPR 2024Bridging Remote Sensors with Multisensor Geospatial Foundation Models
259. CVPR 2024Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology
260. CVPR 2024OpenEQA: Embodied Question Answering in the Era of Foundation Models
261. CVPR 2024Probing the 3D Awareness of Visual Foundation Models
262. ICML 2024Asymmetry in Low-Rank Adapters of Foundation Models
263. ICML 2024Differentially Private Bias-Term Fine-tuning of Foundation Models
264. ICML 2024Foundation Policies with Hilbert Representations
265. ICML 2024Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
266. ICML 2024MOMENT: A Family of Open Time-series Foundation Models
267. ICML 2024Position: On the Societal Impact of Open Foundation Models
268. ICML 2024Position: Why Tabular Foundation Models Should Be a Research Priority
269. ICML 2024Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models
270. ICML 2024Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models
271. ICML 2024To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO
272. ICML 2024Transferring Knowledge From Large Foundation Models to Small Downstream Models
273. NeurIPS 2024$\textit{Read-ME}$: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design
274. NeurIPS 2024$C^2M^3$: Cycle-Consistent Multi-Model Merging
275. NeurIPS 20243-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability
276. NeurIPS 2024A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings
277. NeurIPS 2024A Walsh Hadamard Derived Linear Vector Symbolic Architecture
278. NeurIPS 2024Accelerating Transformers with Spectrum-Preserving Token Merging
279. NeurIPS 2024Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting
280. NeurIPS 2024AdanCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer
281. NeurIPS 2024Adaptive Depth Networks with Skippable Sub-Paths
282. NeurIPS 2024Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment
283. NeurIPS 2024Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning
284. NeurIPS 2024Algebraic Positional Encodings
285. NeurIPS 2024Alias-Free Mamba Neural Operator
286. NeurIPS 2024AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models
287. NeurIPS 2024Amortized Eigendecomposition for Neural Networks
288. NeurIPS 2024Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient
289. NeurIPS 2024Are Self-Attentions Effective for Time Series Forecasting?
290. NeurIPS 2024Asynchronous Perception Machine for Efficient Test Time Training
291. NeurIPS 2024AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
292. NeurIPS 2024B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory
293. NeurIPS 2024BOLD: Boolean Logic Deep Learning
294. NeurIPS 2024Breaking Long-Tailed Learning Bottlenecks: A Controllable Paradigm with Hypernetwork-Generated Diverse Experts
295. NeurIPS 2024Bridging the Divide: Reconsidering Softmax and Linear Attention
296. NeurIPS 2024Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation
297. NeurIPS 2024Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers
298. NeurIPS 2024CALANet: Cheap All-Layer Aggregation for Human Activity Recognition
299. NeurIPS 2024Calibrated Self-Rewarding Vision Language Models
300. NeurIPS 2024Can neural operators always be continuously discretized?

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.