73 citations · 157 across the 15 of their papers we have counts for
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cs.AI2023★ 73 cited
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment
Yang Liu, Yuanshun Yao, Jean-Francois Ton +6
Ensuring alignment, which refers to making models behave in accordance with human intentions [1,2], has become a critical task before deploying large language models (LLMs) in real…
cs.AI2022
Learning to Counterfactually Explain Recommendations
Yuanshun Yao, Chong Wang, Hang Li
Recommender system practitioners are facing increasing pressure to explain recommendations. We explore how to explain recommendations using counterfactual logic, i.e. "Had you not…
cs.AI2022★ 3 cited
Counterfactually Evaluating Explanations in Recommender Systems
Yuanshun Yao, Chong Wang, Hang Li
Modern recommender systems face an increasing need to explain their recommendations. Despite considerable progress in this area, evaluating the quality of explanations remains a si…