Papers by Yuang Wei
Cross-Domain Audio Deepfake Detection: Dataset and Analysis (2024.emnlp-main)
Copied to clipboard
| Challenge: | Existing audio deepfake detection datasets are outdated and lack generalization capabilities. |
| Approach: | They construct a new cross-domain audio deepfake detection dataset comprising over 300 hours of speech data that is generated by five advanced zero-shot TTS models. |
| Outcome: | The proposed models achieve 4.1% and 6.5% error rates in the cross-domain ADD dataset generated by five advanced zero-shot TTS models. |
DoCIA: An Online Document-Level Context Incorporation Agent for Speech Translation (2025.findings-acl)
Copied to clipboard
Xinglin Lyu, Wei Tang, Yuang Li, Xiaofeng Zhao, Ming Zhu, Junhui Li, Yunfei Lu, Min Zhang, Daimeng Wei, Hao Yang, Min Zhang
| Challenge: | Document-level context is crucial for speech translation due to noise from ASR . incorporating document-level contextual information into ST remains a challenge . |
| Approach: | They develop an online framework that integrates document-level context into machine translation . they use document-based modules to integrate document- level context into ST . |
| Outcome: | The proposed framework outperforms baselines in sentence and discourse metrics . it can correct ASR transcription errors and improve translation performance . |
TMATH A Dataset for Evaluating Large Language Models in Generating Educational Hints for Math Word Problems (2025.coling-main)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) are increasingly being applied in education, showing significant potential in personalized instruction, student feedback, and intelligent tutoring systems (ITSs). |
| Approach: | They propose a dataset specifically designed to evaluate LLMs’ ability to generate high-quality hints for Math Word Problems. |
| Outcome: | The proposed dataset shows that LLMs can generate more accurate and contextually appropriate educational hints for math word problems without offering direct answers. |