Alongside huge volumes of research on deep learning models in NLP in the recent years,
there has been much work on benchmark datasets needed to track modeling progress …

Machine Reading Comprehension (MRC) is a challenging task and hot topic in Natural
Language Processing. The goal of this field is to develop systems for answering the …

arXiv:2202.12359v1 [cs.CL] 23 Feb 2022 Page 1 UNIFIEDQA-v2: Stronger Generalization via
Broader Cross-Format Training Daniel Khashabi1 Yeganeh Kordi2 Hannaneh Hajishirzi1,3 …

Multimodal models that jointly process audio and language hold great promise in audio
understanding and are increasingly being adopted in the music domain. By allowing users …

Pre-trained language models have achieved human-level performance on many Machine
Reading Comprehension (MRC) tasks, but it remains unclear whether these models truly …

Zero-shot learning is an approach where models generalize to unseen tasks without direct
training on them. We introduce the Unified Multiple-Choice (UniMC) framework, which is …

In this work, we analyze how human gaze during reading comprehension is conditioned on
the given reading comprehension question, and whether this signal can be beneficial for …

Judging the readability of text has many important applications, for instance when
performing text simplification or when sourcing reading material for language learners. In …

Real-world data often have an open long-tailed distribution, and building a unified QA model
supporting various tasks is vital for practical QA applications. However, it is non-trivial to …

Automatic text simplification (TS) aims to automate the process of rewriting text to make it
easier for people to read. A pre-requisite for TS to be useful is that it should convey …