Glitches in the Attention Matrix

Recent research has focused on addressing artifacts within Transformer models, particularly those arising in the attention matrices that underpin their performance. These artifacts can impair the model's ability to accurately capture dependencies across input sequences, prompting new techniques aimed at refining attention mechanisms to enhance robustness and interpretability.