Papers by Wanyue Zhai
LEMONADE: A Large Multilingual Expert-Annotated Abstractive Event Dataset for the Real World (2025.findings-acl)
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Sina Semnani, Pingyue Zhang, Wanyue Zhai, Haozhuo Li, Ryan Beauchamp, Trey Billing, Katayoun Kishi, Manling Li, Monica Lam
| Challenge: | Using a partially reannotated subset of the Armed Conflict Location & Event Data, we analyze 39,786 conflict events across 20 languages and 171 countries. |
| Approach: | They propose a large-scale conflict event dataset with extensive coverage of region-specific entities. |
| Outcome: | The proposed method detects event arguments and entities through holistic document understanding and normalizes them across the multilingual dataset. |
Adversarial Authorship Attribution for Deobfuscation (2022.acl-long)
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| Challenge: | Existing authorship attribution approaches do not consider adversarial threat model . authors show adversarially trained authorship attributors can degrade effectiveness of existing obfuscators from 20-30% to 5-10% . |
| Approach: | They propose to use rule-based and learning-based text obfuscation approaches to counter authorship attribution. |
| Outcome: | The proposed approaches do not consider the adversarial threat model . authors show that adversarially trained attributors can degrade effectiveness of existing obfuscators from 20-30% to 5-10% . |