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TRIPPULSE: Multi-Agent Travel Planning with Review-Grounded Reasoning

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

Travel itinerary generation requires balancing strict spatio-temporal constraints with human preferences. Existing LLM-based planners mainly rely on structured attributes and pre- defined traveler personas, but real travel deci- sions are often shaped by reviews that reveal experiential factors such as comfort, safety, ser- vice quality, ambiance, crowding, and hidden risks absent from structured databases. Incor- porating such review information is therefore critical to realistic, user-centric itinerary gen- eration. We propose TRIPPULSE1, a multi- agent framework for review-grounded travel p

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Evidence & attribution

First collected: 2026-09-21T06:41:57.136Z. This is not the publication date.