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multi-model-learning

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Master’s thesis: a multimodal transformer that generates personality-aware listener avatars (facial expressions, body and hand gestures) in dyadic conversations. Built with PyTorch using VQ-VAE and transformers, trained on UDIVA. Beats a personality-agnostic baseline on FID and P-FID, and 86% of study participants identified the extroverted avatar.

  • Updated Oct 13, 2026
  • Python

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