arXiv Artificial Intelligence

Behavior2Trip: Towards Personalized Travel Planning via User Behavior Trajectory

Behavior2Trip: Towards Personalized Travel Planning via User Behavior Trajectory

Quick summary

arXiv:2608.26807v1 Announce Type: cross Abstract: Travel planning agents assist users in generating personalized travel plans by modeling their individual preferences. Existing agents either rely on explicit user instructions or engage in multi-turn clarification to elicit user preferences. However, both approaches overlook the rich behavioral signals latent in users' past behaviors, which implicitly encode their preferences. This over-reliance on active user input increases interaction burden and limits plan personalization. To bridge this gap, we introduce a new task, Behavior-Aware Travel P

Key takeaways

  • arXiv:2608.26807v1 Announce Type: cross Abstract: Travel planning agents assist users in generating personalized travel plans by modeling their individual preferences.
  • Existing agents either rely on explicit user instructions or engage in multi-turn clarification to elicit user preferences.
  • However, both approaches overlook the rich behavioral signals latent in users' past behaviors, which implicitly encode their preferences.

Why it matters

The importance of “Behavior2Trip: Towards Personalized Travel Planning via User Behavior Trajectory” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗