AttViz: Online exploration of self-attention for transparent neural language modeling

Understand

Neural language models are becoming the prevailing methodology for the tasks of query answering, text classification, disambiguation, completion and translation.

• Commonly comprised of hundreds of millions of parameters, these neural network models offer state-of-the-art performance at the cost of interpretability; humans are no longer capable of tracing and understanding how decisions are being made.
• The attention mechanism, introduced initially for the task of translation, has been successfully adopted for other language-related tasks.
• We propose AttViz, an online toolkit for exploration of self-attention---real values associated with individual text tokens.