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The model receives a sequence of concepts and learns to predict the next concept. It uses a Transformer-based architecture with additional layers: PreNet : Adjusts concept embeddings for processing.
The architecture of LCMs includes a Concept Encoder, Large Concept Model, and Concept Decoder, focusing on abstract meaning rather than surface-level text structure.
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