Latent Variables

DeepSeek’s MLA (Multi-head Latent Attention) is an improved attention mechanism technique based on the Transformer architecture (combining multi-head attention and latent variables), aimed at enhancing the model’s understanding and processing capabilities of input data. By introducing latent variables and sparse attention, MLA can better capture the hidden structure of input data while reducing computational overhead, … Read more