Showing 2025Show all
3 papers · 1 filter
cs.CL2025
LUMI: Unsupervised Intent Clustering with Multiple Pseudo-Labels
I-Fan Lin, Faegheh Hasibi, Suzan Verberne
In this paper, we propose an intuitive, training-free and label-free method for intent clustering in conversational search. Current approaches to short text clustering use LLM-gene…
cs.CL2025
LLMs Enable Bag-of-Texts Representations for Short-Text Clustering
I-Fan Lin, Faegheh Hasibi, Suzan Verberne
In this paper, we propose a training-free method for unsupervised short text clustering that relies less on careful selection of embedders than other methods. In customer-facing ch…
cs.CL2025
SPILL: Domain-Adaptive Intent Clustering based on Selection and Pooling with Large Language Models
I-Fan Lin, Faegheh Hasibi, Suzan Verberne
In this paper, we propose Selection and Pooling with Large Language Models (SPILL), an intuitive and domain-adaptive method for intent clustering without fine-tuning. Existing embe…