4 papers
Characterizing Bias: Benchmarking Large Language Models in Simplified versus Traditional Chinese
Hanjia Lyu, Jiebo Luo, Jian Kang +1
While the capabilities of Large Language Models (LLMs) have been studied in both Simplified and Traditional Chinese, it is yet unclear whether LLMs exhibit differential performance…
Retrieval Augmentation via User Interest Clustering
Hanjia Lyu, Hanqing Zeng, Yinglong Xia +2
Many existing industrial recommender systems are sensitive to the patterns of user-item engagement. Light users, who interact less frequently, correspond to a data sparsity problem…
Mixture of Weak & Strong Experts on Graphs
Hanqing Zeng, Hanjia Lyu, Diyi Hu +2
Realistic graphs contain both (1) rich self-features of nodes and (2) informative structures of neighborhoods, jointly handled by a Graph Neural Network (GNN) in the typical setup.…
Deceptive Fairness Attacks on Graphs via Meta Learning
Jian Kang, Yinglong Xia, Ross Maciejewski +2
We study deceptive fairness attacks on graphs to answer the following question: How can we achieve poisoning attacks on a graph learning model to exacerbate the bias deceptively? W…