Papers by Sungjin Nam
Scalable and Robust Self-Learning for Skill Routing in Large-Scale Conversational AI Systems (2022.naacl-industry)
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| Challenge: | Existing methods to enable skill routing do not scale in terms of the number of skills and skill on-boarding. |
| Approach: | They propose a model-based approach to enable natural conversation by allowing frequent policy updates . they propose an annotation-based system, rule-based model, and bandit-based learning . |
| Outcome: | The proposed method is scalable and cost-effective, the authors show . they show that it can improve the user experience without abrupt policy changes . |
Finding Educationally Supportive Contexts for Vocabulary Learning with Attention-Based Models (2024.lrec-main)
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| Challenge: | Identifying educationally supportive contexts for vocabulary learning is an important problem to solve for designing effective curricula for contextual word learning. |
| Approach: | They evaluate attention-based approaches to find supportive contexts for vocabulary learning scenarios using an existing benchmark dataset. |
| Outcome: | The proposed model outperforms a generic model and a custom model on a major dataset for educational context support prediction. |