THESIS
2023
1 online resource (x, 47 pages) : color illustrations
Abstract
Computational and cognitive studies suggest that coherence among events is necessary
for understanding events. Most event-understanding tasks ignore coherence among
events and, thus, hinder models from understanding events. In this thesis, we propose
a new task of sub-event generation for an unseen process to evaluate the understanding
of the coherence of sub-event actions and objects. To solve the problem, we design
SubeventWriter, a sub-event sequence generation framework with a coherence controller.
Given an unseen process, the framework can iteratively construct the sub-event sequence
by generating one sub-event at each iteration. We also design a very effective coherence
controller to decode more coherent sub-events. As our extensive experiments and analysis
indicate, SubeventWrite...[
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Computational and cognitive studies suggest that coherence among events is necessary
for understanding events. Most event-understanding tasks ignore coherence among
events and, thus, hinder models from understanding events. In this thesis, we propose
a new task of sub-event generation for an unseen process to evaluate the understanding
of the coherence of sub-event actions and objects. To solve the problem, we design
SubeventWriter, a sub-event sequence generation framework with a coherence controller.
Given an unseen process, the framework can iteratively construct the sub-event sequence
by generating one sub-event at each iteration. We also design a very effective coherence
controller to decode more coherent sub-events. As our extensive experiments and analysis
indicate, SubeventWriter can generate more reliable and meaningful sub-event sequences for unseen processes.
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