Papers by Hai Leong Chieu
Twitter Homophily: Network Based Prediction of User’s Occupation (P19-1)
Copied to clipboard
| Challenge: | Existing approaches to predicting Twitter users' demographic attributes exploit, select, and combine various features generated from text and network to achieve the best performance. |
| Approach: | They extend existing Twitter occupational class prediction data set and exploit social network homophily to achieve competitive performance. |
| Outcome: | The proposed method achieves better performance on a dataset with a small fraction of the training data. |
Colloquial Singaporean English Style Transfer with Fine-Grained Explainable Control (2025.acl-long)
Copied to clipboard
| Challenge: | Existing methods for style transfer between Singlish and Standard English lack explainability and fine-grained control. |
| Approach: | They propose a multi-agent framework where large language models act as expert agents for each linguistic aspect. |
| Outcome: | The proposed model enables precise, interpretable transformations, advancing explainability in NLP for Singlish. |
Coupled Hierarchical Transformer for Stance-Aware Rumor Verification in Social Media Conversations (2020.emnlp-main)
Copied to clipboard
| Challenge: | Existing approaches to rumor verification and stance classification fail to exploit intertask dependencies . |
| Approach: | They propose a Hierarchical Transformer model which uses BERT to obtain thread representations . they propose 'coupled' transformer modules to capture intertask interactions and a post-level attention layer to use predicted stance labels for RV. |
| Outcome: | The proposed model outperforms existing methods on two benchmark datasets. |
Guiding Computational Stance Detection with Expanded Stance Triangle Framework (2023.acl-long)
Copied to clipboard
| Challenge: | Experimental results show that strategically-enriched data can significantly improve the performance on out-of-domain and cross-target evaluation. |
| Approach: | They propose to decompose a stance detection task from a theoretical perspective and extend it with additional annotations. |
| Outcome: | The proposed task improves performance on out-of-domain and cross-target evaluations using a linguistic framework. |
Cross-Topic Rumor Detection using Topic-Mixtures (2021.eacl-main)
Copied to clipboard
| Challenge: | Existing work on rumor detection models has explored network structures, propagation paths, user credibility and fusion of heterogeneous data. |
| Approach: | They propose a method that adapts a rumor detection model trained on source to target topics to make rumour predictions. |
| Outcome: | The proposed method outperforms baseline debiasing methods in a cross-topic setting. |