Papers by Chih Yao Chen

2 papers
HonestBait: Forward References for Attractive but Faithful Headline Generation (2023.findings-acl)

Copied to clipboard

Challenge: Current approaches to generating attractive headlines often learn directly from data based on clicks and views . clickbait models fail to reveal how much interest is raised by the writing style and how much is due to the event or topic itself .
Approach: They propose a framework for generating headlines using forward references . they use a dataset containing pairs of fake news and verified news .
Outcome: The proposed framework yields more attractive headlines while maintaining high veracity . the framework is based on a dataset containing fake news with verified news .
Label-Aware Hyperbolic Embeddings for Fine-grained Emotion Classification (2023.acl-long)

Copied to clipboard

Challenge: Existing models only address text classification problem in the euclidean space, which is not optimal . e.g., fear and terrified labels may not be differentiated in such space, harming performance .
Approach: They propose a framework that can integrate hyperbolic embeddings to improve the task . they learn label embeddements in the hyperbolical space and then add them to the framework .
Outcome: The proposed framework improves fine-grained emotion classification on two benchmark datasets with 3% improvement over previous state-of-the-art models.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations