2 citations · 2 across the 4 of their papers we have counts for
4 papers
Correlated Errors in Large Language Models
Elliot Kim, Avi Garg, Kenny Peng +1
Diversity in training data, architecture, and providers is assumed to mitigate homogeneity in LLMs. However, we lack empirical evidence on whether different LLMs differ meaningfull…
A No Free Lunch Theorem for Human-AI Collaboration
Kenny Peng, Nikhil Garg, Jon Kleinberg
The gold standard in human-AI collaboration is complementarity -- when combined performance exceeds both the human and algorithm alone. We investigate this challenge in binary clas…
Wisdom and Foolishness of Noisy Matching Markets
Kenny Peng, Nikhil Garg
We consider a many-to-one matching market where colleges share true preferences over students but make decisions using only independent noisy rankings. Each student has a true valu…
Reconciling the accuracy-diversity trade-off in recommendations
Kenny Peng, Manish Raghavan, Emma Pierson +2
In recommendation settings, there is an apparent trade-off between the goals of accuracy (to recommend items a user is most likely to want) and diversity (to recommend items repres…