Attention-aware semantic relevance predicting Chinese sentence reading

arXiv:2403.18542v1 Announce Type: cross
Abstract: In recent years, several influential computational models and metrics have been proposed to predict how humans comprehend and process sentence. One particularly promising approach is contextual semantic similarity. Inspired by the attention algorithm in Transformer and human memory mechanisms, this study proposes an ``attention-aware'' approach for computing contextual semantic relevance. This new approach takes into account the different contributions of contextual parts and the expectation effect, allowing it to incorporate contextual information fully. The attention-aware …

abstract algorithm arxiv attention chinese computational computing cs.cl cs.lg human humans memory metrics process reading semantic study transformer type