4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.IR2024★ 2 cited
Language-Model Prior Overcomes Cold-Start Items
Shiyu Wang, Hao Ding, Yupeng Gu +3
The growth of recommender systems (RecSys) is driven by digitization and the need for personalized content in areas such as e-commerce and video streaming. The content in these sys…
cs.AI2024★ 4 cited
Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs
Behnam Rahdari, Hao Ding, Ziwei Fan +4
The unique capabilities of Large Language Models (LLMs), such as the natural language text generation ability, position them as strong candidates for providing explanation for reco…
cs.IR2023★ 1 cited
Pre-trained Recommender Systems: A Causal Debiasing Perspective
Ziqian Lin, Hao Ding, Nghia Trong Hoang +3
Recent studies on pre-trained vision/language models have demonstrated the practical benefit of a new, promising solution-building paradigm in AI where models can be pre-trained on…