AI RESEARCH
Collab-REC: An LLM-based Agentic Framework for Balancing Recommendations in Tourism
arXiv CS.AI
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ArXi:2508.15030v5 Announce Type: replace 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 agent's viewpoint is represented while reducing spurious or repeated outputs.