Multi-level Contrastive Learning for Script-based Character
  Understanding
Dawei Li Hengyuan Zhang Yanran Li Shiping Yang
In this work, we tackle the scenario of understanding characters in scripts,
which aims to learn the characters' personalities and identities from their
utterances. We begin by analyzing several challenges in this scenario, and then
propose a multi-level contrastive learning framework to capture characters'
global information in a fine-grained manner. To validate the proposed
framework, we conduct extensive experiments on three character understanding
sub-tasks by comparing with strong pre-trained language models, including
SpanBERT, Longformer, BigBird and ChatGPT-3.5. Experimental results demonstrate
that our method improves the performances by a considerable margin. Through
further in-depth analysis, we show the effectiveness of our method in
addressing the challenges and provide more hints on the scenario of character
understanding. We will open-source our work on github at
https://github.com/David-Li0406/Script-based-Character-Understanding.