Event schemas are a form of world knowledge about the typical progression of events.
Recent methods for event schema induction use information extraction systems to construct …

Emerging events, such as the COVID pandemic and the Ukraine Crisis, require a time-
sensitive comprehensive understanding of the situation to allow for appropriate decision …

As an essential task in information extraction (IE), Event-Event Causal Relation Extraction
(ECRE) aims to identify and classify the causal relationships between event mentions in …

Event schema depicts the typical structure of complex events, serving as a scaffolding to
effectively analyze, predict, and possibly intervene in the ongoing events. To induce event …

Event understanding aims at understanding the content and relationship of events within
texts, which covers multiple complicated information extraction tasks: event detection, event …

Schema induction builds a graph representation explaining how events unfold in a scenario.
Existing approaches have been based on information retrieval (IR) and information …

We study an emerging and intriguing problem of multimodal temporal event forecasting with
large language models. Compared to using text or graph modalities, the investigation of …

Script learning studies how daily events unfold. Previous works tend to consider a script as a
linear sequence of events while ignoring the potential branches that arise due to people's …

Event grounding aims at linking mention references in text corpora to events from a
knowledge base (KB). Previous work on this task focused primarily on linking to a single KB …

Although pairwise causal relations have been extensively studied in observational
longitudinal analyses across many disciplines, incorporating knowledge of causal pairs into …