Learnable Attention Priors Fix the Attention Sink Problem: What GOAT Reveals

According to the paper "You Need Better Attention Priors: Introducing GOAT" by Elon Litman and Gabe Guo, standard Transformer attention mechanisms waste representational capacity by defaulting to the first token when no relevant information exists - the attention sink problem. This means our production LLMs are fighting a mathematical handicap we can now fix.