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LLMs can be harnessed to refine neural topic models, yielding substantial gains in topic quality and interpretability without sacrificing document representation accuracy.
The Linguistic eXtractor (LX) is introduced, a fine-tuned, large language model trained on consumer-authored text that also has been labeled with consumers'self-reported ratings of 16 consumption-related emotions and four evaluation constructs: trust, commitment, recommendation, and sentiment.
