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 9 of 11

401. NeurIPS 2024Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization
402. NeurIPS 2024ProxyFusion: Face Feature Aggregation Through Sparse Experts
403. NeurIPS 2024Q-VLM: Post-training Quantization for Large Vision-Language Models
404. NeurIPS 2024QT-ViT: Improving Linear Attention in ViT with Quadratic Taylor Expansion
405. NeurIPS 2024QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space Model
406. NeurIPS 2024QUEST: Quadruple Multimodal Contrastive Learning with Constraints and Self-Penalization
407. NeurIPS 2024Real-time Core-Periphery Guided ViT with Smart Data Layout Selection on Mobile Devices
408. NeurIPS 2024Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
409. NeurIPS 2024Reinforced Cross-Domain Knowledge Distillation on Time Series Data
410. NeurIPS 2024Relating Hopfield Networks to Episodic Control
411. NeurIPS 2024Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling
412. NeurIPS 2024Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints
413. NeurIPS 2024Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting
414. NeurIPS 2024Rethinking Imbalance in Image Super-Resolution for Efficient Inference
415. NeurIPS 2024Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models
416. NeurIPS 2024Retrieval & Fine-Tuning for In-Context Tabular Models
417. NeurIPS 2024Revisiting motion information for RGB-Event tracking with MOT philosophy
418. NeurIPS 2024Revisiting the Integration of Convolution and Attention for Vision Backbone
419. NeurIPS 2024RMLR: Extending Multinomial Logistic Regression into General Geometries
420. NeurIPS 2024Robustly overfitting latents for flexible neural image compression
421. NeurIPS 2024Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching
422. NeurIPS 2024Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD Prompts
423. NeurIPS 2024S2HPruner: Soft-to-Hard Distillation Bridges the Discretization Gap in Pruning
424. NeurIPS 2024Scaling Law for Time Series Forecasting
425. NeurIPS 2024Scaling White-Box Transformers for Vision
426. NeurIPS 2024Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
427. NeurIPS 2024Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations
428. NeurIPS 2024Selective Attention: Enhancing Transformer through Principled Context Control
429. NeurIPS 2024Separations in the Representational Capabilities of Transformers and Recurrent Architectures
430. NeurIPS 2024Set-based Neural Network Encoding Without Weight Tying
431. NeurIPS 2024ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
432. NeurIPS 2024SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusion
433. NeurIPS 2024Single Image Reflection Separation via Dual-Stream Interactive Transformers
434. NeurIPS 2024Slot State Space Models
435. NeurIPS 2024SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion
436. NeurIPS 2024Spectral Adapter: Fine-Tuning in Spectral Space
437. NeurIPS 2024Spiking Token Mixer: An event-driven friendly Former structure for spiking neural networks
438. NeurIPS 2024START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation
439. NeurIPS 2024Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning
440. NeurIPS 2024SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors
441. NeurIPS 2024SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention
442. NeurIPS 2024The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
443. NeurIPS 2024The Expressive Capacity of State Space Models: A Formal Language Perspective
444. NeurIPS 2024The Mamba in the Llama: Distilling and Accelerating Hybrid Models
445. NeurIPS 2024The Selective $G$-Bispectrum and its Inversion: Applications to $G$-Invariant Networks
446. NeurIPS 2024Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks
447. NeurIPS 2024Theoretical Foundations of Deep Selective State-Space Models
448. NeurIPS 2024TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
449. NeurIPS 2024Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
450. NeurIPS 2024Towards Croppable Implicit Neural Representations

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.