视觉语言预训练论文趋势 2023–2026

主要结论

• 视觉语言预训练论文从 2023 年的 65 篇增长到 2026 年的 87 篇，三年间扩大到约 1.3 倍。
• NeurIPS 是发视觉语言预训练论文最多的会议，2023–2026 年共 93 篇，占四个会议总量的 35%。
• 交叉方向里涨得最快的是应用 · computer vision：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 9 篇。
• 在「开放词汇视觉」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的视觉定位是 4.3 倍，视觉语言预训练是 1.3 倍。

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

• NeurIPS 2026Benchmarking Optimizers for Large Language Model Pretraining
• ICML 2026How Does the Pretraining Distribution Shape In-Context Learning? A Fundamental Trade-Off
• ICLR 2026PonderLM: Pretraining Language Models to Ponder in Continuous Space
• CVPR 2026Large-scale Codec Avatars The Unreasonable Effectiveness of Large-scale Avatar Pretraining
• NeurIPS 2025ADPretrain: Advancing Industrial Anomaly Detection via Anomaly Representation Pretraining
• ICML 2025Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging
• ICLR 2025Attributing Culture-Conditioned Generations to Pretraining Corpora
• CVPR 2025MAP: Unleashing Hybrid Mamba-Transformer Vision Backbone's Potential with Masked Autoregressive Pretraining
• NeurIPS 2024Data curation via joint example selection further accelerates multimodal learning
• ICML 2024Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
• ICLR 2024Demystifying CLIP Data
• CVPR 2024ParameterNet: Parameters Are All You Need for Large-scale Visual Pretraining of Mobile Networks
• NeurIPS 2023Bootstrapping Vision-Language Learning with Decoupled Language Pre-training
• ICML 2023Contrastive Learning Meets Homophily: Two Birds with One Stone
• ICLR 2023Energy-Inspired Self-Supervised Pretraining for Vision Models
• CVPR 2023Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning Paradigm
• NeurIPS 2026C3P: Contrastive promoter-protein pretraining yields representations capturing bacterial gene regulation
• ICML 2026Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
• ICLR 2026MICLIP: Learning to Interpret Representation in Vision Models
• CVPR 2026The Surprising Effectiveness of Noise Pretraining for Implicit Neural Representations

全部视觉语言预训练论文

共 263 篇，第 1 / 6 页

1. CVPR 2026b-CLIP Text-Conditioned Contrastive Learning for Multi-Granular Vision-Language Alignment
2. CVPR 2026BabyVLM-V2 Toward Developmentally Grounded Pretraining and Benchmarking of Vision Foundation
3. CVPR 2026Beyond 3D VQAs Injecting 3D Spatial Priors into Vision-Language Models
4. CVPR 2026CLEP Contrastive Language-Pose Pretraining
5. CVPR 2026Concept-Aware Batch Sampling Improves Language-Image Pretraining
6. CVPR 2026EthoCLIP Ontology-Enhanced Video-Language Pretraining for Animal Behavior Understanding
7. CVPR 2026Evo-1 Lightweight Vision-Language-Action Model with Preserved Semantic Alignment
8. CVPR 2026FALCON False-Negative Aware Learning of Contrastive Negatives in Vision-Language Alignment
9. CVPR 2026From Panel to Pixel Zoom-In Vision-Language Pretraining from Biomedical Scientific
10. CVPR 2026Improving Calibration in Test-Time Prompt Tuning for Vision-Language Models via
11. CVPR 2026Joint-Aligned Latent Action Towards Scalable VLA Pretraining in the Wild
12. CVPR 2026LA-Pose Latent Action Pretraining Meets Pose Estimation
13. CVPR 2026Large-scale Codec Avatars The Unreasonable Effectiveness of Large-scale Avatar Pretraining
14. CVPR 2026Learning from Itself Mining Internal Knowledge from Vision Language Models
15. CVPR 2026MedKCO Medical Vision-Language Pretraining via Knowledge-Driven Cognitive Orchestration
16. CVPR 2026Modeling Cross-vision Synergy for Unified Large Vision Model
17. CVPR 2026MuViT Multi-Resolution Vision Transformers for Learning Across Scales in Microscopy
18. CVPR 2026PowerCLIP Powerset Alignment for Contrastive Pre-Training
19. CVPR 2026Scaling Parallel Sequence Models to Vision Foundation Models
20. CVPR 2026Selective Amnesia using Contrastive Subnet Erasure for Class Level Unlearning
21. CVPR 2026Spatial-Aware VLA Pretraining through Visual-Physical Alignment from Human Videos
22. CVPR 2026The Surprising Effectiveness of Noise Pretraining for Implicit Neural Representations
23. CVPR 2026TIPSv2 Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment
24. CVPR 2026Towards Highly Transferable Vision-Language Attack via Semantic-Augmented Dynamic Contrastive Interaction
25. CVPR 2026Uncertainty-guided Compositional Alignment with Part-to-Whole Semantic Representativeness in Hyperbolic Vision-Language
26. CVPR 2026UniRefiner Teaching Pre-trained ViTs to Self-Dispose Dross via Contrastive Register
27. CVPR 2026Unlearning without Forgetting Securely Removing Targeted Concepts from Large-Scale Vision-Language
28. ICLR 2026CLIP Behaves like a Bag-of-Words Model Cross-modally but not Uni-modally
29. ICLR 2026CortiLife: A Unified Framework for Cortical Representation Learning across the Lifespan
30. ICLR 2026D2E: Scaling Vision-Action Pretraining on Desktop Data for Transfer to Embodied AI
31. ICLR 2026Genomic Foundationless Models: Pretraining Does Not Promise Performance
32. ICLR 2026GranViT: A Fine-Grained Vision Model With Autoregressive Perception For MLLMs
33. ICLR 2026Investigating Redundancy in Multimodal Large Language Models with Multiple Vision Encoders
34. ICLR 2026Learning Facts at Scale with Active Reading
35. ICLR 2026MICLIP: Learning to Interpret Representation in Vision Models
36. ICLR 2026PonderLM: Pretraining Language Models to Ponder in Continuous Space
37. ICLR 2026Reward Models Inherit Value Biases from Pretraining
38. ICLR 2026ScaleCap: Scalable Image Captioning via Dual-Modality Debiasing
39. ICLR 2026Self-Augmented Visual Contrastive Decoding
40. ICLR 2026Train Once, Answer All: Many Pretraining Experiments for the Cost of One
41. ICLR 2026When Priors Backfire: On the Vulnerability of Unlearnable Examples to Pretraining
42. ICML 2026A Theory of Contrastive Learning with Natural Images
43. ICML 2026Beyond Blind Noising: Disentangled Visual Rectification for Hallucination Mitigation in MLLMs
44. ICML 2026Beyond Logits: Coherent Hallucination Mitigation via Attention Contrastive Decoding
45. ICML 2026BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining
46. ICML 2026Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise
47. ICML 2026DEGAP: Dynamic Entropy-Guided Attention Perturbation for Contrastive Decoding in Large Vision-Language Models
48. ICML 2026Disease-Centric Vision-Language Pretraining with Hybrid Visual Encoding for 3D Computed Tomography
49. ICML 2026Facts in Stats: Impacts of Pretraining Diversity on Language Model Generalization
50. ICML 2026How Does the Pretraining Distribution Shape In-Context Learning? A Fundamental Trade-Off

常见问题

2023–2026 年四大会议一共有多少篇视觉语言预训练论文？

共 263 篇，按年份分别是 2023 年 65 篇、2024 年 55 篇、2025 年 56 篇、2026 年 87 篇。

NeurIPS 2026 有多少篇视觉语言预训练论文？

NeurIPS 2026 有 27 篇视觉语言预训练论文，上一届是 26 篇。

ICLR 2026 有多少篇视觉语言预训练论文？

ICLR 2026 有 14 篇视觉语言预训练论文，上一届是 17 篇。

ICML 2026 有多少篇视觉语言预训练论文？

ICML 2026 有 19 篇视觉语言预训练论文，上一届是 3 篇。

CVPR 2026 有多少篇视觉语言预训练论文？

CVPR 2026 有 27 篇视觉语言预训练论文，上一届是 10 篇。

哪个会议的视觉语言预训练论文最多？

NeurIPS，2023–2026 年共 93 篇。