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 8 of 11

351. NeurIPS 2024Improving Neural ODE Training with Temporal Adaptive Batch Normalization
352. NeurIPS 2024In Pursuit of Causal Label Correlations for Multi-label Image Recognition
353. NeurIPS 2024Incorporating Test-Time Optimization into Training with Dual Networks for Human Mesh Recovery
354. NeurIPS 2024Infinite-Dimensional Feature Interaction
355. NeurIPS 2024Initializing Variable-sized Vision Transformers from Learngene with Learnable Transformation
356. NeurIPS 2024Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting
357. NeurIPS 2024Is Multiple Object Tracking a Matter of Specialization?
358. NeurIPS 2024Kraken: Inherently Parallel Transformers For Efficient Multi-Device Inference
359. NeurIPS 2024L-TTA: Lightweight Test-Time Adaptation Using a Versatile Stem Layer
360. NeurIPS 2024LaSCal: Label-Shift Calibration without target labels
361. NeurIPS 2024Latent Functional Maps: a spectral framework for representation alignment
362. NeurIPS 2024Learning diverse causally emergent representations from time series data
363. NeurIPS 2024Learning from Highly Sparse Spatio-temporal Data
364. NeurIPS 2024Learning Group Actions on Latent Representations
365. NeurIPS 2024Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees
366. NeurIPS 2024Learning symmetries via weight-sharing with doubly stochastic tensors
367. NeurIPS 2024Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios
368. NeurIPS 2024Linearly Decomposing and Recomposing Vision Transformers for Diverse-Scale Models
369. NeurIPS 2024LinNet: Linear Network for Efficient Point Cloud Representation Learning
370. NeurIPS 2024LLM-AutoDA: Large Language Model-Driven Automatic Data Augmentation for Long-tailed Problems
371. NeurIPS 2024MambaTree: Tree Topology is All You Need in State Space Model
372. NeurIPS 2024Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages
373. NeurIPS 2024MatFormer: Nested Transformer for Elastic Inference
374. NeurIPS 2024MatrixNet: Learning over symmetry groups using learned group representations
375. NeurIPS 2024Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
376. NeurIPS 2024MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers
377. NeurIPS 2024MeshXL: Neural Coordinate Field for Generative 3D Foundation Models
378. NeurIPS 2024Meta-Learning Universal Priors Using Non-Injective Change of Variables
379. NeurIPS 2024MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map
380. NeurIPS 2024Mixtures of Experts for Audio-Visual Learning
381. NeurIPS 2024MoEUT: Mixture-of-Experts Universal Transformers
382. NeurIPS 2024MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
383. NeurIPS 2024Monomial Matrix Group Equivariant Neural Functional Networks
384. NeurIPS 2024MoVA: Adapting Mixture of Vision Experts to Multimodal Context
385. NeurIPS 2024Multi-Head Mixture-of-Experts
386. NeurIPS 2024Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times
387. NeurIPS 2024Neural Experts: Mixture of Experts for Implicit Neural Representations
388. NeurIPS 2024NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
389. NeurIPS 2024On Feature Learning in Structured State Space Models
390. NeurIPS 2024On Sampling Strategies for Spectral Model Sharding
391. NeurIPS 2024Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling
392. NeurIPS 2024Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation
393. NeurIPS 2024Parallelizing Linear Transformers with the Delta Rule over Sequence Length
394. NeurIPS 2024Pedestrian-Centric 3D Pre-collision Pose and Shape Estimation from Dashcam Perspective
395. NeurIPS 2024Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers
396. NeurIPS 2024Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis
397. NeurIPS 2024PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting
398. NeurIPS 2024PointMamba: A Simple State Space Model for Point Cloud Analysis
399. NeurIPS 2024Poseidon: Efficient Foundation Models for PDEs
400. NeurIPS 2024PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond

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.