6 citations · 6 across the 3 of their papers we have counts for
3 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…
Auditing Cross-Cultural Consistency of Human-Annotated Labels for Recommendation Systems
Rock Yuren Pang, Jack Cenatempo, Franklyn Graham +5
Recommendation systems increasingly depend on massive human-labeled datasets; however, the human annotators hired to generate these labels increasingly come from homogeneous backgr…
Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysis
J. D. Zamfirescu-Pereira, Jerry Chen, Emily Wen +3
Algorithms provide powerful tools for detecting and dissecting human bias and error. Here, we develop machine learning methods to to analyze how humans err in a particular high-sta…