mlsanityData to 7 Oct 2026

Zero-Shot Learning Through Cross-Modal Transfer

arXiv 1301.3666 ↗First posted 16 Jan 2013cs.CV cs.LGcited by 237

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Cited by 21 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

This work introduces a model that can recognize objects in images even if no training data is available for the objects. The only necessary knowledge about the unseen categories comes from unsupervised large text corpora. In our zero-shot framework distributional information in language can be seen as spanning a semantic basis for understanding what objects look like. Most previous zero-shot learning models can only differentiate between unseen classes. In contrast, our model can both obtain state of the art performance on classes that have thousands of training images and obtain reasonable performance on unseen classes. This is achieved by first using outlier detection in the semantic space and then two separate recognition models. Furthermore, our model does not require any manually defined semantic features for either words or images.

Key facts. Cited by 237 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Jan 2013.

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Citing papers per year: 2021: 69; 2022: 66; 2023: 45; 2024: 27; 2025: 18; 2026: 12.

237 papers.

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  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021Learning to Prompt for Vision-Language Modelscited by 2,269
  3. 2022Conditional Prompt Learning for Vision-Language Modelscited by 1,427
  4. 2022Visual Classification via Description from Large Language Modelscited by 331
  5. 2022Simple Open-Vocabulary Object Detection with Vision Transformerscited by 303
  6. 2022Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Expertscited by 202
  7. 2022Versatile Diffusion: Text, Images and Variations All in One Diffusion Modelcited by 199
  8. 2021Combined Scaling for Zero-shot Transfer Learningcited by 182
  9. 2021Synthesis of Compositional Animations from Textual Descriptionscited by 177
  10. 2022DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detectioncited by 176
  11. 2021Align and Prompt: Video-and-Language Pre-training with Entity Promptscited by 149
  12. 2021MultiBench: Multiscale Benchmarks for Multimodal Representation Learningcited by 143
38 more
  1. 2022Task Residual for Tuning Vision-Language Modelscited by 122
  2. 2022Foundations and Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questionscited by 116
  3. 2021Learning Graph Embeddings for Compositional Zero-shot Learningcited by 112
  4. 2023CLIPood: Generalizing CLIP to Out-of-Distributionscited by 96
  5. 2021Contrastive Embedding for Generalized Zero-Shot Learningcited by 94
  6. 2022Debiased Learning from Naturally Imbalanced Pseudo-Labelscited by 85
  7. 2022K-LITE: Learning Transferable Visual Models with External Knowledgecited by 79
  8. 2022Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddingscited by 75
  9. 2023BadCLIP: Trigger-Aware Prompt Learning for Backdoor Attacks on CLIPcited by 63
  10. 2023Frozen Language Model Helps ECG Zero-Shot Learningcited by 62
  11. 2021Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Searchcited by 57
  12. 2021Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Cloudscited by 55
  13. 2021Subspace Regularizers for Few-Shot Class Incremental Learningcited by 54
  14. 2022I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classificationcited by 54
  15. 2022Mixed Differential Privacy in Computer Visioncited by 53
  16. 2022Multitask Vision-Language Prompt Tuningcited by 51
  17. 2021Opening up Open-World Trackingcited by 50
  18. 2021Learning Graph Embeddings for Open World Compositional Zero-Shot Learningcited by 49
  19. 2023Introducing Language Guidance in Prompt-based Continual Learningcited by 49
  20. 2022Open-environment Machine Learningcited by 48
  21. 2023Enhancing CLIP with GPT-4: Harnessing Visual Descriptions as Promptscited by 48
  22. 2022Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Biascited by 43
  23. 2021Knowledge-aware Zero-Shot Learning: Survey and Perspectivecited by 41
  24. 2021SIGN: Spatial-information Incorporated Generative Network for Generalized Zero-shot Semantic Segmentationcited by 41
  25. 2022American == White in Multimodal Language-and-Image AIcited by 39
  26. 2021AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognitioncited by 36
  27. 2021Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directionscited by 35
  28. 2022Peekaboo: Text to Image Diffusion Models are Zero-Shot Segmentorscited by 34
  29. 2022High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learningcited by 31
  30. 2022Evidence for Hypodescent in Visual Semantic AIcited by 30
  31. 2021Dual-Awareness Attention for Few-Shot Object Detectioncited by 29
  32. 2022Markedness in Visual Semantic AIcited by 29
  33. 2023Learning Attention as Disentangler for Compositional Zero-shot Learningcited by 29
  34. 2022VGSE: Visually-Grounded Semantic Embeddings for Zero-Shot Learningcited by 27
  35. 2022I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classificationcited by 27
  36. 2023Multi-modal Machine Learning in Engineering Design: A Review and Future Directionscited by 27
  37. 2021Semantics-Guided Contrastive Network for Zero-Shot Object detectioncited by 26
  38. 2021Dual Progressive Prototype Network for Generalized Zero-Shot Learningcited by 26

50 most cited of 237 All 237 (JSON)