A lack of corpora has so far limited advances in integrating human gaze data as a
supervisory signal in neural attention mechanisms for natural language processing (NLP) …

Learned self-attention functions in state-of-the-art NLP models often correlate with human
attention. We investigate whether self-attention in large-scale pre-trained language models …

Eye‐tracking data from reading provide a structured signal with a fine‐grained temporal
resolution which closely follows the sequential structure of the text. It is highly correlated with …

Neural code summarization leverages deep learning models to automatically generate brief
natural language summaries of code snippets. The development of Transformer models has …

Determining the relative importance of the elements in a sentence is a key factor for
effortless natural language understanding. For human language processing, we can …

Eye movement recordings from reading are one of the richest signals of human language
processing. Corpora of eye movements during reading of contextualized running text is a …

When speakers describe an image, they tend to look at objects before mentioning them. In
this paper, we investigate such sequential cross-modal alignment by modelling the image …

NLP models are imperfect and lack intricate capabilities that humans access automatically
when processing speech or reading a text. Human language processing data can be …

Gaze behaviour has been used as a way to gather cognitive information for a number of
years. In this paper, we discuss the use of gaze behaviour in solving different tasks in natural …

It has been shown that multilingual transformer models are able to predict human reading
behavior when fine-tuned on small amounts of eye tracking data. As the cumulated …