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I-Fan Lin

2 accepted papers

2025

SPILL: Domain-Adaptive Intent Clustering based on Selection and Pooling with Large Language Models

ACL 2025finding

In this paper, we propose Selection and Pooling with Large Language Models (SPILL), an intuitive, domain-adaptive method for intent clustering without fine-tuning. Existing embeddings-based clustering methods rely on a few labeled examples or unsupervised fine-tuning to optimize results for each new…

2024

Generate then Refine: Data Augmentation for Zero-shot Intent Detection

EMNLP 2024finding

In this short paper we propose a data augmentation method for intent detection in zero-resource domains.Existing data augmentation methods rely on few labelled examples for each intent category, which can be expensive in settings with many possible intents.We use a two-stage approach: First, we gene…