Papers by Yufeng Diao
“Barking up the Right Tree”, a GAN-Based Pun Generation Model through Semantic Pruning (2024.lrec-main)
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| Challenge: | Existing methods for generating humorous puns are limited and require a broad spectrum of commonsense and worldly skills. |
| Approach: | They propose a GAN-based approach that employs semantic pruning and contrastive learning to generate humorous puns using a model that captures the semantic nuances of puns. |
| Outcome: | The proposed model produces semantically coherent and humorous puns while ensuring both correctness and humor. |
Giving Control Back to Models: Enabling Offensive Language Detection Models to Autonomously Identify and Mitigate Biases (2024.findings-emnlp)
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| Challenge: | Existing models often rely on specific words to predict offensive content, compromising model fairness and potentially exacerbates biases against vulnerable and minority groups. |
| Approach: | They propose a bias self-awareness and data self-iteration framework to help models identify and mitigate biases by integrating multiple natural language processing techniques. |
| Outcome: | The proposed framework reduces false positive rate of models in in-distribution and out-of-difference tests, enhances model accuracy and fairness, and shows promising performance improvements on larger datasets. |
Hate Speech Detection Based on Sentiment Knowledge Sharing (2021.acl-long)
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| Challenge: | Existing methods for hate speech detection are stereotyped and biased . et al., a paper examining the effectiveness of multitask learning in hate speech recognition tasks . |
| Approach: | They propose a hate speech detection framework based on sentiment knowledge sharing . they extract affective features of the target sentence and use sentiment features from external resources . |
| Outcome: | The proposed model can detect hate speech over two public datasets. |
WECA: A WordNet-Encoded Collocation-Attention Network for Homographic Pun Recognition (D18-1)
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Yufeng Diao, Hongfei Lin, Di Wu, Liang Yang, Kan Xu, Zhihao Yang, Jian Wang, Shaowu Zhang, Bo Xu, Dongyu Zhang
| Challenge: | Homographic puns have a long history in human writing, widely used in written and spoken literature, which intended as jokes. |
| Approach: | They propose a WordNet-encoded model to settle polysemy of homographic puns and a word weighted model for recognizing them. |
| Outcome: | The proposed model can distinguish between homographic pun and non-homographic pun texts. |