Papers by Libin Zheng

2 papers
Domain Adaptation for Subjective Induction Questions Answering on Products by Adversarial Disentangled Learning (2024.acl-long)

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Challenge: Existing methods to answer subjective questions about products are often imbalanced across product domains.
Approach: They propose a domain-adaptive model that integrates multiple viewpoints into a good answer by integrating these heterogeneous and inconsistent viewpoints.
Outcome: The proposed model integrates multiple viewpoints into a single answer span and is able to integrate them into the answer.
Generating Deep Questions with Commonsense Reasoning Ability from the Text by Disentangled Adversarial Inference (2023.findings-acl)

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Challenge: Existing methods for commonsense question generation produce shallow questions that can be answered by simple word matching.
Approach: They propose a task of commonsense question generation that aims to yield deep-level questions from the text.
Outcome: The proposed model can yield deep-level and to-the-point questions from the text.

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