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SynthTRIPs: A Knowledge-Grounded Framework for Benchmark Query Generation for Personalized Tourism Recommenders
In this work, we explore using Large Language Models (LLMs) to generate synthetic travel queries that emulate diverse user personas and incorporate structured filters such as budget constraints and sustainability preferences.
Enhancing Tourism Recommender Systems for Sustainable City Trips Using Retrieval-Augmented Generation
Tourism Recommender Systems (TRS) have traditionally focused on providing personalized travel suggestions, often prioritizing user preferences without considering broader sustainability goals.
Beats of Bias: Analyzing Lyrics with Topic Modeling and Gender Bias Measurements
This paper uses topic modeling and bias measurement techniques to analyze and determine gender bias in English song lyrics.
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