Papers by Yu-Chien Tang
RSVP: Customer Intent Detection via Agent Response Contrastive and Generative Pre-Training (2023.findings-emnlp)
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| Challenge: | Existing intent detection approaches have relied on adaptively pre-training language models with large-scale datasets, yet the predominant cost of data collection may hinder their superiority. |
| Approach: | They propose a self-supervised framework dedicated to task-oriented dialogues which incorporates agent responses for pre-training in a two-stage manner. |
| Outcome: | The proposed framework outperforms the state-of-the-art frameworks for task-oriented dialogues on two real-world customer service datasets. |
MathEDU: Feedback Generation on Problem-Solving Processes for Mathematical Learning Support (2026.eacl-long)
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| Challenge: | Existing studies have examined the reliability of Large Language Models (LLMs) in grading authentic student problem solving processes and delivering effective feedback. |
| Approach: | They propose to use a dataset to evaluate the reliability of large language models in mathematics and a teacher-written feedback system to improve student problem-solving processes. |
| Outcome: | The proposed model improves in correctness classification, error identification, and feedback generation, but generates a gap from teacher-written feedback. |