Papers with Situated conversational recommendation

1 papers
Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation (2026.acl-long)

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Challenge: Situated conversational recommendation (SCR) uses visual scenes grounded in specific environments and natural language dialogue to deliver contextually appropriate recommendations.
Approach: They propose a framework that integrates scene transition estimation and Bayesian inverse inference to provide contextually appropriate recommendations.
Outcome: The proposed framework achieves superiority over baselines on two representative benchmarks on dynamic scene transitions and implicit user intents.

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