35 citations · 60 across the 14 of their papers we have counts for
5 papers · 1 filter
Interpretable Triplet Importance for Personalized Ranking
Bowei He, Chen Ma
Personalized item ranking has been a crucial component contributing to the performance of recommender systems. As a representative approach, pairwise ranking directly optimizes the…
Bi-Chainer: Automated Large Language Models Reasoning with Bidirectional Chaining
Shuqi Liu, Bowei He, Linqi Song
Large Language Models (LLMs) have shown human-like reasoning abilities but still face challenges in solving complex logical problems. Existing unidirectional chaining methods, such…
Privacy in LLM-based Recommendation: Recent Advances and Future Directions
Sichun Luo, Wei Shao, Yuxuan Yao +9
Nowadays, large language models (LLMs) have been integrated with conventional recommendation models to improve recommendation performance. However, while most of the existing works…
No Time to Train: Empowering Non-Parametric Networks for Few-shot 3D Scene Segmentation
Xiangyang Zhu, Renrui Zhang, Bowei He +6
To reduce the reliance on large-scale datasets, recent works in 3D segmentation resort to few-shot learning. Current 3D few-shot segmentation methods first pre-train models on 'see…
Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networks
Ziqiang Cui, Xing Tang, Yang Qiao +4
Estimating the individual treatment effect (ITE) from observational data is a crucial research topic that holds significant value across multiple domains. How to identify hidden co…