Papers by Chau Pham
TopicGPT: A Prompt-based Topic Modeling Framework (2024.naacl-long)
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| Challenge: | TopicGPT uses large language models to uncover latent topics in text . topic models represent topics as bags of words that require "reading the tea leaves" topic models also offer limited control over formatting and specificity of topics . |
| Approach: | TopicGPT uses large language models to uncover latent topics in text . authors propose a prompt-based framework that produces topics that align better with human categorizations . |
| Outcome: | TopicGPT produces topics that align better with human categorizations compared to competing methods. |
Emotion analysis and detection during COVID-19 (2022.lrec-1)
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| Challenge: | 3,000 English tweets labeled with emotions are used to predict emotions during crises . authors propose semi-supervised learning to bridge this gap . |
| Approach: | They propose to use a dataset of 3,000 English tweets labeled with emotions . they propose semi-supervised learning to bridge this gap by analyzing unlabeled data . |
| Outcome: | The proposed model can be used to predict emotions in the context of COVID-19 . the proposed model performs better than other models using unlabeled data . |
Suri: Multi-constraint Instruction Following in Long-form Text Generation (2024.findings-emnlp)
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| Challenge: | Existing studies on instruction following focus on simple instructions and short responses . however, there are challenges associated with collecting preference judgments on long-form texts . |
| Approach: | They propose an instruction-following alignment method that uses dispreferred instructions to obtain negative feedback from dispvoted instructions. |
| Outcome: | The proposed model generates significantly longer texts than base models without significant quality degradation. |