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Explains the full architecture of Transformers and the self-attention mechanism, highlighting the paradigm shift towards using completely pretrained models.
Explores a unified framework for understanding and evaluating generative sequence models of DNA/RNA or Protein, covering topics like coevolution, conservation, and different models such as GREMLIN and BERT.
Explores neuro-symbolic representations for understanding commonsense knowledge and reasoning, emphasizing the challenges and limitations of deep learning in natural language processing.
