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Unifying Generative and Dense Retrieval for Sequential Recommendation
Liu Yang, Fabian Paischer, Kaveh Hassani +11
Sequential dense retrieval models utilize advanced sequence learning techniques to compute item and user representations, which are then used to rank relevant items for a user thro…
Preference Discerning with LLM-Enhanced Generative Retrieval
Fabian Paischer, Liu Yang, Linfeng Liu +12
In sequential recommendation, models recommend items based on user's interaction history. To this end, current models usually incorporate information such as item descriptions and…
Proactive Detection and Calibration of Seasonal Advertisements with Multimodal Large Language Models
Hamid Eghbalzadeh, Shuai Shao, Saurabh Verma +5
A myriad of factors affect large scale ads delivery systems and influence both user experience and revenue. One such factor is proactive detection and calibration of seasonal adver…