University · Artificial Intelligence · AI Research Methods and Capstone

Multimodal AI Research: Combining Vision, Language, and Audio

4 Abschnitte

Foundations of multimodal learning: early, late, and cross-modal fusion; contrastive pre-training (CLIP, ALIGN); vision-language models (DALL-E, Flamingo, LLaVA); audio-visual learning; challenges of grounding, alignment, and evaluation; and ethical considerations in multimodal generative AI research.

Inhaltsübersicht

  • Foundations of Multimodal Learning
  • Contrastive Pre-training: CLIP, ALIGN, and Multimodal Representation Learning
  • Vision-Language Models: Flamingo, LLaVA, and Multimodal Generation
  • Multimodal Evaluation, Audio-Visual Learning, and Ethical Considerations
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