Online articles using striking headlines that promise intriguing information are often used to
attract readers. Most of the time, the information provided in the text is disappointing to the …

In this paper, we investigate which questions are challenging for retrieval-based Question
Answering (QA). We (i) propose retrieval complexity (RC), a novel metric conditioned on the …

Recent years have seen impressive progress in AI-assisted writing, yet the developments in
AI-assisted reading are lacking. We propose inline commentary as a natural vehicle for AI …

In recent years, the DBLP computer science bibliography has been prominently used for
searching scholarly information, such as publications, scholars, and venues. However, its …

The continuous development of Question Answering (QA) datasets has drawn the research
community's attention toward multi-domain models. A popular approach is to use multi …

Question Answering (QA) systems are increasingly deployed in applications where they
support real-world decisions. However, state-of-the-art models rely on deep neural …

Transfer learning has recently become the dominant paradigm of natural language
processing. Models pre-trained on unlabeled data can be fine-tuned for downstream tasks …

This project addresses the gap between the escalating volume of English-to-Turkish
Wikipedia translations and the insufficient number of contributors, particularly in technical …