5 citations · 10 across the 6 of their papers we have counts for
4 papers · 1 filter
Diversity Recommendation via Causal Deconfounding of Co-purchase Relations and Counterfactual Exposure
Jingmao Zhang, Zhiting Zhao, Yunqi Lin +4
Beyond user-item modeling, item-to-item relationships are increasingly used to enhance recommendation. However, common methods largely rely on co-occurrence, making them prone to i…
Dual-Phase Playtime-guided Recommendation: Interest Intensity Exploration and Multimodal Random Walks
Jingmao Zhang, Zhiting Zhao, Yunqi Lin +4
The explosive growth of the video game industry has created an urgent need for recommendation systems that can scale with expanding catalogs and maintain user engagement. While pri…
Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects
Zihan Hong, Yushi Wu, Zhiting Zhao +4
With the recent progress in generative artificial intelligence (Generative AI), particularly in the development of large language models, recommendation systems are evolving to bec…
RocketEval: Efficient Automated LLM Evaluation via Grading Checklist
Tianjun Wei, Wei Wen, Ruizhi Qiao +2
Evaluating large language models (LLMs) in diverse and challenging scenarios is essential to align them with human preferences. To mitigate the prohibitive costs associated with hu…