← Search

Rui Ke

2 accepted papers

2026

CATCH: A Controllable Theme Detection Framework with Contextualized Clustering and Hierarchical Generation

AAAI 2026technical

Theme detection is a fundamental task in user-centric dialogue systems, aiming to identify the latent topic of each utterance without relying on predefined schemas. Unlike intent induction, which operates within fixed label spaces, theme detection requires cross-dialogue consistency and alignment wi

Cited by 0SourcePDFScholar
2025

Take the essence and discard the dross: A Rethinking on Data Selection for Fine-Tuning Large Language Models

NAACL 2025long

Data selection for fine-tuning large language models (LLMs) aims to choose a high-quality subset from existing datasets, allowing the trained model to outperform baselines trained on the full dataset. However, the expanding body of research lacks a clear, unified framework, and the variability in ex…

Cited by 5SourcePDFScholar