Papers by Yun-Zhu Song
Beyond Detection: A Defend-and-Summarize Strategy for Robust and Interpretable Rumor Analysis on Social Media (2023.emnlp-main)
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| Challenge: | Existing detection models for rumors detection are poor interpretability and lack the textual content to detect rumors. |
| Approach: | They propose a framework that analyzes the textual content and propagation paths of rumors on social media and provides multi-perspective prediction explanations. |
| Outcome: | The proposed framework defends against malicious attacks and provides prediction explanations on three public datasets. |
Improving Multi-Document Summarization through Referenced Flexible Extraction with Credit-Awareness (2022.naacl-main)
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| Challenge: | Existing approaches to Multi-document summarization are limited due to the extremely long input length. |
| Approach: | They propose an extract-then-abstract Transformer framework to overcome the problem . they leverage pre-trained language models to construct hierarchical extractors and abstractors . |
| Outcome: | The proposed framework outperforms baseline models with comparable model sizes and achieves the best results on the Multi-News, Multi-XScience, and WikiCatSum corpora. |
Adversary-Aware Rumor Detection (2021.findings-acl)
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| Challenge: | Existing rumor detection models do not detect malicious attacks, e.g., framing. |
| Approach: | They propose a weighted-edge transformer-graph network and position-aware Adversarial Response Generator to improve the vulnerability of detection models. |
| Outcome: | The proposed framework achieves state-of-the-art on various rumor detection tasks and maintains performance under adversarial learning. |