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Re2A: Situated Conversational Recommendation via Rubric-based Preference Reasoning and Alignment

arXiv · AI, language, vision and robotics · article · Sep 16, 2026 · UTC

Real-world recommendation scenarios are commonly grounded in shared physical environments during user-recommender interactions. This motivates situated conversational recommendation (SCR), a complex task requiring recommender assistants to jointly reason over dialogue history, co-observed scenes, and in-scene item attributes. However, current approaches struggle with this setting due to two intertwined challenges: accurately understanding situated user preferences throughout the conversation and generating responses that simultaneously satisfy user needs and grounded situations. To this end, w

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