8 citations · 12 across the 4 of their papers we have counts for
4 papers
Reward Models Inherit Value Biases from Pretraining
Brian Christian, Jessica A. F. Thompson, Elle Michelle Yang +4
Reward models (RMs) are central to aligning large language models (LLMs) with human values but have received less attention than pretrained and post-trained LLMs themselves. Becaus…
Self-Blinding and Counterfactual Self-Simulation Mitigate Biases and Sycophancy in Large Language Models
Brian Christian, Matan Mazor
Fair decisions require ignoring irrelevant, potentially biasing, information. To achieve this, decision-makers need to approximate what decision they would have made had they not k…
Reward Model Interpretability via Optimal and Pessimal Tokens
Brian Christian, Hannah Rose Kirk, Jessica A. F. Thompson +2
Reward modeling has emerged as a crucial component in aligning large language models with human values. Significant attention has focused on using reward models as a means for fine…
Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online
Steven Adler, Zoë Hitzig, Shrey Jain +29
Anonymity is an important principle online. However, malicious actors have long used misleading identities to conduct fraud, spread disinformation, and carry out other deceptive sc…