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 10 of 11

451. NeurIPS 2024Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models
452. NeurIPS 2024Understanding and Minimising Outlier Features in Transformer Training
453. NeurIPS 2024Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective
454. NeurIPS 2024Understanding the Differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
455. NeurIPS 2024Understanding Transformer Reasoning Capabilities via Graph Algorithms
456. NeurIPS 2024UNIT: Unifying Image and Text Recognition in One Vision Encoder
457. NeurIPS 2024UniTS: A Unified Multi-Task Time Series Model
458. NeurIPS 2024Universal Neural Functionals
459. NeurIPS 2024Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis
460. NeurIPS 2024VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks
461. NeurIPS 2024Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights
462. NeurIPS 2024xLSTM: Extended Long Short-Term Memory
463. NeurIPS 2024YOLOv10: Real-Time End-to-End Object Detection
464. NeurIPS 2024You Only Cache Once: Decoder-Decoder Architectures for Language Models
465. ICML 2023$\pi$-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation
466. ICML 2023A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models
467. ICML 2023CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks
468. ICML 2023Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models
469. ICML 2023Learning Unnormalized Statistical Models via Compositional Optimization
470. ICML 2023Magneto: A Foundation Transformer
471. ICML 2023On the Power of Foundation Models
472. NeurIPS 20234M: Massively Multimodal Masked Modeling
473. NeurIPS 2023A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints
474. NeurIPS 2023ADGym: Design Choices for Deep Anomaly Detection
475. NeurIPS 2023Agnostically Learning Single-Index Models using Omnipredictors
476. NeurIPS 2023An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions
477. NeurIPS 2023BayesTune: Bayesian Sparse Deep Model Fine-tuning
478. NeurIPS 2023Beyond Confidence: Reliable Models Should Also Consider Atypicality
479. NeurIPS 2023BiMatting: Efficient Video Matting via Binarization
480. NeurIPS 2023Birth of a Transformer: A Memory Viewpoint
481. NeurIPS 2023Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
482. NeurIPS 2023C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models
483. NeurIPS 2023CHAMMI: A benchmark for channel-adaptive models in microscopy imaging
484. NeurIPS 2023Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task
485. NeurIPS 2023Contextually Affinitive Neighborhood Refinery for Deep Clustering
486. NeurIPS 2023Differentiable Random Partition Models
487. NeurIPS 2023Distributed Inference and Fine-tuning of Large Language Models Over The Internet
488. NeurIPS 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
489. NeurIPS 2023Efficient Equivariant Transfer Learning from Pretrained Models
490. NeurIPS 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
491. NeurIPS 2023Energy Transformer
492. NeurIPS 2023Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance
493. NeurIPS 2023Evaluating Neuron Interpretation Methods of NLP Models
494. NeurIPS 2023Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
495. NeurIPS 2023Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models
496. NeurIPS 2023Foundation Model is Efficient Multimodal Multitask Model Selector
497. NeurIPS 2023FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models
498. NeurIPS 2023Generalized Logit Adjustment: Calibrating Fine-tuned Models by Removing Label Bias in Foundation Models
499. NeurIPS 2023Generating QM1B with PySCF$_{\text{IPU}}$
500. NeurIPS 2023GEO-Bench: Toward Foundation Models for Earth Monitoring

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.