Papers by Shu-Ting Pi
REIC: RAG-Enhanced Intent Classification at Scale (2025.emnlp-industry)
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Ziji Zhang, Michael Yang, Zhiyu Chen, Yingying Zhuang, Shu-Ting Pi, Qun Liu, Rajashekar Maragoud, Vy Nguyen, Anurag Beniwal
| Challenge: | Accurate intent classification is critical for efficient routing in customer service . however, as companies expand their product lines, intent classification faces scalability challenges . |
| Approach: | They propose a retrieval-augmented generation Enhanced Intent Classification approach which leverages retrieval augmented generation to integrate relevant knowledge into a model. |
| Outcome: | The proposed approach outperforms fine-tuning, zero-shot, and few-shot methods on real-world datasets. |
Don’t Shoot The Breeze: Topic Continuity Model Using Nonlinear Naive Bayes With Attention (2024.emnlp-industry)
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| Challenge: | Large-scale language models (LLMs) are becoming increasingly popular in business scenarios, but maintaining topic continuity is a challenge. |
| Approach: | They propose a topic continuity model that assesses whether a response aligns with the initial conversation topic using a Naive Bayes approach. |
| Outcome: | The proposed model outperforms existing models in handling lengthy and complex conversations. |