Question answering over temporal knowledge graphs (KGs) efficiently uses facts contained
in a temporal KG, which records entity relations and when they occur in time, to answer …

Human reading comprehension often requires reasoning of event semantic relations in
narratives, represented by Event-centric Question-Answering (QA). To address event-centric …

Time-Sensitive Question Answering (TSQA) demands the effective utilization of specific
temporal contexts, encompassing multiple time-evolving facts, to address time-sensitive …

In this study, we explore an emerging research area of Continual Learning for Temporal
Sensitive Question Answering (CLTSQA). Previous research has primarily focused on …

Accurately understanding temporal relations between events is a critical building block of
diverse tasks, such as temporal reading comprehension (TRC) and relation extraction …

Temporal reasoning over tabular data presents substantial challenges for large language
models (LLMs), as evidenced by recent research. In this study, we conduct a comprehensive …

We propose a simple yet effective strategy to incorporate event knowledge extracted from
event trigger annotations via posterior regularization to improve the event reasoning …

We present a novel task of document-level script event prediction, which aims to predict the
next event given a candidate list of narrative events in long-form documents. To enable this …

Structured information is generally easier to store, understand, and utilize compared to
unstructured text. Extracting structured information from unstructured text and applying this …