One of the key challenges of automatic story generation is how to generate a long narrative
that can maintain fluency, relevance, and coherence. Despite recent progress, current story …

Representations of events described in text are important for various tasks. In this work, we
present SWCC: a Simultaneous Weakly supervised Contrastive learning and Clustering …

To improve the performance of long text generation, recent studies have leveraged
automatically planned event structures (ie storylines) to guide story generation. Such prior …

Despite recent advancements, existing story generation systems continue to encounter
difficulties in effectively incorporating contextual and event features, which greatly influence …

We explore the idea of incorporating concepts from writing skills curricula into human-
machine collaborative writing scenarios, focusing on adding writing modes as a control for …

With recent advances in large language models (LLMs), the concept of automatically
generating children's educational materials has become increasingly realistic. Working …

A human author can write any length of story without losing coherence. Also, they always
bring the story to a proper ending, an ability that current language models lack. In this work …

Event extraction aims to extract information of triggers and arguments from texts. Recent
advanced methods leverage information from other modalities (eg, images and videos) …

Understanding the speaker's intended meaning often involves drawing commonsense
inferences to reason about what is not stated explicitly. In multi-event sentences, it requires …

Event representing methods usually use external knowledge to construct potentially more
useful positive or negative samples, while neglecting the importance of sampling them …