13th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’26)

Abstract

The 13th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’26), held in conjunction with RecSys, adopts a human-centered perspective on recommender systems in an era shaped by Large Language Models (LLMs), agentic AI, and generative interfaces. The workshop positions recommender systems not only as ranking engines, but as socio-technical decision-support systems whose value depends on transparency, controllability, inclusiveness, and measurable benefit for users. IntRS’26 brings together researchers from recommender systems, HCI, NLP, psychology, and cognitive science to study how interaction paradigms such as conversational interfaces, explanation-rich user interfaces, multimodal interaction, and mixed-initiative workflows influence trust, preference construction, cognitive effort, and decision quality. By connecting the historical focus of IntRS with emerging challenges related to LLM integration, hallucinations, persuasion, fairness, and accountability, the workshop aims to articulate a rigorous research agenda for next-generation human-centered recommender systems.