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 6 of 6

251. NeurIPS 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
252. NeurIPS 2023Efficient Equivariant Transfer Learning from Pretrained Models
253. NeurIPS 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
254. NeurIPS 2023Energy Transformer
255. NeurIPS 2023Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance
256. NeurIPS 2023Evaluating Neuron Interpretation Methods of NLP Models
257. NeurIPS 2023Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
258. NeurIPS 2023Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models
259. NeurIPS 2023Foundation Model is Efficient Multimodal Multitask Model Selector
260. NeurIPS 2023FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models
261. NeurIPS 2023Generalized Logit Adjustment: Calibrating Fine-tuned Models by Removing Label Bias in Foundation Models
262. NeurIPS 2023Generating QM1B with PySCF$_{\text{IPU}}$
263. NeurIPS 2023GEO-Bench: Toward Foundation Models for Earth Monitoring
264. NeurIPS 2023Geometry-Aware Adaptation for Pretrained Models
265. NeurIPS 2023Global Optimality in Bivariate Gradient-based DAG Learning
266. NeurIPS 2023Grassmann Manifold Flows for Stable Shape Generation
267. NeurIPS 2023Guiding The Last Layer in Federated Learning with Pre-Trained Models
268. NeurIPS 2023Large Language Models can Implement Policy Iteration
269. NeurIPS 2023Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition
270. NeurIPS 2023Learning Sample Difficulty from Pre-trained Models for Reliable Prediction
271. NeurIPS 2023LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition
272. NeurIPS 2023Module-wise Adaptive Distillation for Multimodality Foundation Models
273. NeurIPS 2023Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine
274. NeurIPS 2023Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes
275. NeurIPS 2023On Learning Latent Models with Multi-Instance Weak Supervision
276. NeurIPS 2023Paxion: Patching Action Knowledge in Video-Language Foundation Models
277. NeurIPS 2023Quantification of Uncertainty with Adversarial Models
278. NeurIPS 2023RADAR: Robust AI-Text Detection via Adversarial Learning
279. NeurIPS 2023RanPAC: Random Projections and Pre-trained Models for Continual Learning
280. NeurIPS 2023Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests
281. NeurIPS 2023Rethinking Gauss-Newton for learning over-parameterized models
282. NeurIPS 2023Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models
283. NeurIPS 2023Segment Any Point Cloud Sequences by Distilling Vision Foundation Models
284. NeurIPS 2023Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models
285. NeurIPS 2023Semantic HELM: A Human-Readable Memory for Reinforcement Learning
286. NeurIPS 2023Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models
287. NeurIPS 2023SSL4EO-L: Datasets and Foundation Models for Landsat Imagery
288. NeurIPS 2023STEVE-1: A Generative Model for Text-to-Behavior in Minecraft
289. NeurIPS 2023Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models
290. NeurIPS 2023The Learnability of In-Context Learning
291. NeurIPS 2023The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit
292. NeurIPS 2023Top-Ambiguity Samples Matter: Understanding Why Deep Ensemble Works in Selective Classification
293. NeurIPS 2023Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning
294. NeurIPS 2023Towards Label-free Scene Understanding by Vision Foundation Models
295. NeurIPS 2023Unbiased learning of deep generative models with structured discrete representations
296. NeurIPS 2023VanillaNet: the Power of Minimalism in Deep Learning
297. NeurIPS 2023What Do Deep Saliency Models Learn about Visual Attention?
298. NeurIPS 2023Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
299. NeurIPS 2023Your representations are in the network: composable and parallel adaptation for large scale models

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.