23 citations · 27 across the 2 of their papers we have counts for
8 papers
Toward Diverse Precondition Generation
Heeyoung Kwon, Nathanael Chambers, Niranjan Balasubramanian
Language understanding must identify the logical connections between events in a discourse, but core events are often unstated due to their commonsense nature. This paper fills in…
TellMeWhy: A Dataset for Answering Why-Questions in Narratives
Yash Kumar Lal, Nathanael Chambers, Raymond Mooney +1
Answering questions about why characters perform certain actions is central to understanding and reasoning about narratives. Despite recent progress in QA, it is not clear if exist…
Conditional Generation of Temporally-ordered Event Sequences
Shih-Ting Lin, Nathanael Chambers, Greg Durrett
Models of narrative schema knowledge have proven useful for a range of event-related tasks, but they typically do not capture the temporal relationships between events. We propose…
Modeling Preconditions in Text with a Crowd-sourced Dataset
Heeyoung Kwon, Mahnaz Koupaee, Pratyush Singh +5
Preconditions provide a form of logical connection between events that explains why some events occur together and information that is complementary to the more widely studied rela…
Modeling Label Semantics for Predicting Emotional Reactions
Radhika Gaonkar, Heeyoung Kwon, Mohaddeseh Bastan +2
Predicting how events induce emotions in the characters of a story is typically seen as a standard multi-label classification task, which usually treats labels as anonymous classes…
Generating Narrative Text in a Switching Dynamical System
Noah Weber, Leena Shekhar, Heeyoung Kwon +2
Early work on narrative modeling used explicit plans and goals to generate stories, but the language generation itself was restricted and inflexible. Modern methods use language mo…