8 citations · 13 across the 6 of their papers we have counts for
6 papers
Adaptive Candidate Retrieval with Dynamic Knowledge Graph Construction for Cold-Start Recommendation
Wooseong Yang, Weizhi Zhang, Yuqing Liu +4
The cold-start problem remains a critical challenge in real-world recommender systems, as new items with limited interaction data or insufficient information are frequently introdu…
LLMInit: A Free Lunch from Large Language Models for Selective Initialization of Recommendation
Weizhi Zhang, Liangwei Yang, Wooseong Yang +5
Collaborative filtering (CF) is widely adopted in industrial recommender systems (RecSys) for modeling user-item interactions across numerous applications, but often struggles with…
Uncertainty in Graph Neural Networks: A Survey
Fangxin Wang, Yuqing Liu, Kay Liu +3
Graph Neural Networks (GNNs) have been extensively used in various real-world applications. However, the predictive uncertainty of GNNs stemming from diverse sources such as inhere…
Rec-GPT4V: Multimodal Recommendation with Large Vision-Language Models
Yuqing Liu, Yu Wang, Lichao Sun +1
The development of large vision-language models (LVLMs) offers the potential to address challenges faced by traditional multimodal recommendations thanks to their proficient unders…
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation
Xiaohan Li, Yuqing Liu, Zheng Liu +1
Session-based Recommendation (SBR) is to predict users' next interested items based on their previous browsing sessions. Existing methods model sessions as graphs or sequences to e…
Using the Newton-Raphson Method with Automatic Differentiation to Numerically Solve Implied Volatility of Stock Option through Binomial Model
Wanchaloem Wunkaew, Yuqing Liu, Kirill V. Golubnichiy
In the paper written by Klibanov et al, it proposes a novel method to calculate implied volatility of a European stock options as a solution to ill-posed inverse problem for the Bl…