16 citations · 22 across the 5 of their papers we have counts for
5 papers
Underwriting the Agent Economy: The Blueprint for an AI Insurance Stack
Cristian Trout, Sanmi Koyejo, Sasha Romanosky +34
From maritime trade to commercial nuclear power, insurance has been the enabler of major economic and technological developments by pricing risk, limiting downside, and spreading b…
A Good Plan is Hard to Find: Aligning Models with Preferences is Misaligned with What Helps Users
Nishant Balepur, Matthew Shu, Yoo Yeon Sung +5
To assist users in complex tasks, LLMs generate plans: step-by-step instructions towards a goal. While alignment methods aim to ensure LLM plans are helpful, they train (RLHF) or e…
Comparing Apples to Oranges: A Taxonomy for Navigating the Global Landscape of AI Regulation
Sacha Alanoca, Shira Gur-Arieh, Tom Zick +1
AI governance has transitioned from soft law, such as national AI strategies and voluntary guidelines, to binding regulation at an unprecedented pace. This evolution has produced a…
AI Procurement Checklists: Revisiting Implementation in the Age of AI Governance
Tom Zick, Mason Kortz, David Eaves +1
Public sector use of AI has been quietly on the rise for the past decade, but only recently have efforts to regulate it entered the cultural zeitgeist. While simple to articulate,…
RewardBench: Evaluating Reward Models for Language Modeling
Nathan Lambert, Valentina Pyatkin, Jacob Morrison +9
Reward models (RMs) are at the crux of successfully using RLHF to align pretrained models to human preferences, yet there has been relatively little study that focuses on evaluatio…