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 …

We analyze if large language models are able to predict patterns of human reading
behavior. We compare the performance of language-specific and multilingual pretrained …

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 …

We present WebQAmGaze, a multilingual low-cost eye-tracking-while-reading dataset,
designed as the first webcam-based eye-tracking corpus of reading to support the …

This paper is interested in investigating whether human gaze signals can be leveraged to
improve state-of-the-art search engine performance and how to incorporate this new input …

Spurious correlations were found to be an important factor explaining model performance in
various NLP tasks (eg, gender or racial artifacts), often considered to be''shortcuts''to the …

In text classification, the traditional attention mechanisms usually focus too much on frequent
words, and need extensive labeled data in order to learn. This article proposes a …

摘要语言理解是认知科学和计算机科学交叉领域共同关心的问题, 但两个学科在选择具体研究
问题时却十分不同. 认知科学领域的研究侧重解析大脑的工作机制, 更多地关注于描述大脑对 …

In this work, we use question answering as a general framework for studying how eye
movements in reading reflect the reader's goals, how they are pursued, and the extent to …

Research on human reading has long documented that reading behavior shows task-
specific effects, but it has been challenging to build general models predicting what reading …