Verifying complex political claims is a challenging task, especially when politicians use
various tactics to subtly misrepresent the facts. Automatic fact-checking systems fall short …

Thanks to the effectiveness and wide availability of modern pretrained language models
(PLMs), recently proposed approaches have achieved remarkable results in dependency …

The integration of multi-document pre-training objectives into language models has resulted
in remarkable improvements in multi-document downstream tasks. In this work, we propose …

Asking questions about a situation is an inherent step towards understanding it. To this end,
we introduce the task of role question generation, which, given a predicate mention and a …

In this work, we investigate transfer learning from semantic role labeling (SRL) to event
argument extraction (EAE), considering their similar argument structures. We view the …

The remarkable performance boost of artificial intelligence (AI) algorithms is a result of re-
emergence of deep neural networks that have been applied in a diverse set of applications …

Multi-text applications, such as multi-document summarization, are typically required to
model redundancies across related texts. Current methods confronting consolidation …

Despite significant advances in Semantic Role Labeling (SRL), much work in this field has
been carried out with a focus on verbal predicates, with the research on nominal SRL …

Although we have witnessed impressive progress in Semantic Role Labeling (SRL), most of
the research in the area is carried out assuming that the majority of predicates are verbs …

There has been an increasing interest in detecting hallucinations in model-generated texts,
both manually and automatically, at varying levels of granularity. However, most existing …