深度学习 · foundation models论文趋势 2023–2026

ICML/NeurIPS 深度学习方向：foundation_models

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 536 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

深度学习 · foundation models论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
20236507072
20241920116209
202515653478
20262781357177

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

全部深度学习 · foundation models论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 299 篇，第 6 / 6 页

  1. NeurIPS 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
  2. NeurIPS 2023Efficient Equivariant Transfer Learning from Pretrained Models
  3. NeurIPS 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
  4. NeurIPS 2023Energy Transformer
  5. NeurIPS 2023Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance
  6. NeurIPS 2023Evaluating Neuron Interpretation Methods of NLP Models
  7. NeurIPS 2023Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
  8. NeurIPS 2023Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models
  9. NeurIPS 2023Foundation Model is Efficient Multimodal Multitask Model Selector
  10. NeurIPS 2023FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models
  11. NeurIPS 2023Generalized Logit Adjustment: Calibrating Fine-tuned Models by Removing Label Bias in Foundation Models
  12. NeurIPS 2023Generating QM1B with PySCF$_{\text{IPU}}$
  13. NeurIPS 2023GEO-Bench: Toward Foundation Models for Earth Monitoring
  14. NeurIPS 2023Geometry-Aware Adaptation for Pretrained Models
  15. NeurIPS 2023Global Optimality in Bivariate Gradient-based DAG Learning
  16. NeurIPS 2023Grassmann Manifold Flows for Stable Shape Generation
  17. NeurIPS 2023Guiding The Last Layer in Federated Learning with Pre-Trained Models
  18. NeurIPS 2023Large Language Models can Implement Policy Iteration
  19. NeurIPS 2023Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition
  20. NeurIPS 2023Learning Sample Difficulty from Pre-trained Models for Reliable Prediction
  21. NeurIPS 2023LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition
  22. NeurIPS 2023Module-wise Adaptive Distillation for Multimodality Foundation Models
  23. NeurIPS 2023Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine
  24. NeurIPS 2023Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes
  25. NeurIPS 2023On Learning Latent Models with Multi-Instance Weak Supervision
  26. NeurIPS 2023Paxion: Patching Action Knowledge in Video-Language Foundation Models
  27. NeurIPS 2023Quantification of Uncertainty with Adversarial Models
  28. NeurIPS 2023RADAR: Robust AI-Text Detection via Adversarial Learning
  29. NeurIPS 2023RanPAC: Random Projections and Pre-trained Models for Continual Learning
  30. NeurIPS 2023Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests
  31. NeurIPS 2023Rethinking Gauss-Newton for learning over-parameterized models
  32. NeurIPS 2023Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models
  33. NeurIPS 2023Segment Any Point Cloud Sequences by Distilling Vision Foundation Models
  34. NeurIPS 2023Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models
  35. NeurIPS 2023Semantic HELM: A Human-Readable Memory for Reinforcement Learning
  36. NeurIPS 2023Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models
  37. NeurIPS 2023SSL4EO-L: Datasets and Foundation Models for Landsat Imagery
  38. NeurIPS 2023STEVE-1: A Generative Model for Text-to-Behavior in Minecraft
  39. NeurIPS 2023Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models
  40. NeurIPS 2023The Learnability of In-Context Learning
  41. NeurIPS 2023The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit
  42. NeurIPS 2023Top-Ambiguity Samples Matter: Understanding Why Deep Ensemble Works in Selective Classification
  43. NeurIPS 2023Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning
  44. NeurIPS 2023Towards Label-free Scene Understanding by Vision Foundation Models
  45. NeurIPS 2023Unbiased learning of deep generative models with structured discrete representations
  46. NeurIPS 2023VanillaNet: the Power of Minimalism in Deep Learning
  47. NeurIPS 2023What Do Deep Saliency Models Learn about Visual Attention?
  48. NeurIPS 2023Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
  49. NeurIPS 2023Your representations are in the network: composable and parallel adaptation for large scale models

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用 paperlist 查深度学习 · foundation models在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？

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常见问题

2023–2026 年四大会议一共有多少篇深度学习 · foundation models论文？
共 536 篇，按年份分别是 2023 年 72 篇、2024 年 209 篇、2025 年 78 篇、2026 年 177 篇。
NeurIPS 2026 有多少篇深度学习 · foundation models论文？
NeurIPS 2026 有 27 篇深度学习 · foundation models论文，上一届是 15 篇。
ICLR 2026 有多少篇深度学习 · foundation models论文？
ICLR 2026 有 8 篇深度学习 · foundation models论文，上一届是 6 篇。
ICML 2026 有多少篇深度学习 · foundation models论文？
ICML 2026 有 135 篇深度学习 · foundation models论文，上一届是 53 篇。
CVPR 2026 有多少篇深度学习 · foundation models论文？
CVPR 2026 有 7 篇深度学习 · foundation models论文，上一届是 4 篇。
哪个会议的深度学习 · foundation models论文最多？
NeurIPS，2023–2026 年共 299 篇。

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