1 citations · 1 across the 2 of their papers we have counts for
7 papers
The Politician, the Liar, and the Obedient Worker: Emerging Behavior of LLM Agents in Hierarchical Games
Fatemeh Seyedin, Adrian Weller, Jinhyuk Yun +1
LLMs are rapidly embedding themselves into daily life: drafting our emails, managing our schedules, and making decisions on our behalf. As they move from individual tools to partic…
Unequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AI
Holli Sargeant, Mackenzie Jorgensen, Arina Shah +3
Uncertainty in artificial intelligence (AI) predictions raises pressing legal and ethical questions for AI-assisted decision-making. This article examines two uncertainty-based alg…
Human agency in initial human-AI proof formalization workflows
Katherine M. Collins, Simon Frieder, Jonas Bayer +14
For centuries, human mathematicians have written proofs to substantiate their mathematical arguments; yet, the ability to automatically verify the validity of proofs has long been…
Documenting Deployment with Fabric: A Repository of Real-World AI Governance
Mackenzie Jorgensen, Kendall Brogle, Katherine M. Collins +10
Artificial intelligence (AI) is increasingly integrated into society, from financial services and traffic management to creative writing. Academic literature on the deployment of A…
Large Language Models Must Be Taught to Know What They Don't Know
Sanyam Kapoor, Nate Gruver, Manley Roberts +7
When using large language models (LLMs) in high-stakes applications, we need to know when we can trust their predictions. Some works argue that prompting high-performance LLMs is s…
When Should We Orchestrate Multiple Agents?
Umang Bhatt, Sanyam Kapoor, Mihir Upadhyay +6
Strategies for orchestrating the interactions between multiple agents, both human and artificial, can wildly overestimate performance and underestimate the cost of orchestration. W…