Papers with LLM-based refinements

1 papers
LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models (2026.acl-long)

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Challenge: Existing cross-lingual topic models depend on sparse bilingual resources and often yield incoherent or weakly aligned topics.
Approach: They propose a framework that integrates LLM-guided topic refinement with self-consistency uncertainty quantification to enable black-box, stable, and scalable enhancement of cross-lingual topic models.
Outcome: Experiments on multilingual corpora show that the proposed framework achieves superior topic coherence and alignment while reducing reliance on bilingual dictionaries and expensive LLM calls.

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