HCAILGMar 10, 2025

Roamify: Designing and Evaluating an LLM Based Google Chrome Extension for Personalised Itinerary Planning

arXiv:2504.10489v14 citationsh-index: 2
Originality Synthesis-oriented
AI Analysis

This addresses travel planning for general users, but it is incremental as it applies existing LLMs to a specific domain.

The authors tackled travel planning by developing Roamify, an AI-powered Chrome extension that uses LLMs like Llama and T5 to generate personalized itineraries based on user preferences and web-scraped data, with user surveys showing a preference for AI over existing methods across all age groups.

In this paper, we present Roamify, an Artificial Intelligence powered travel assistant that aims to ease the process of travel planning. We have tested and used multiple Large Language Models like Llama and T5 to generate personalised itineraries per user preferences. Results from user surveys highlight the preference for AI powered mediums over existing methods to help in travel planning across all user age groups. These results firmly validate the potential need of such a travel assistant. We highlight the two primary design considerations for travel assistance: D1) incorporating a web-scraping method to gather up-to-date news articles about destinations from various blog sources, which significantly improves our itinerary suggestions, and D2) utilising user preferences to create customised travel experiences along with a recommendation system which changes the itinerary according to the user needs. Our findings suggest that Roamify has the potential to improve and simplify how users across multiple age groups plan their travel experiences.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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