24 citations · 26 across the 3 of their papers we have counts for
3 papers
cs.AI2024★ 24 cited
Alignment faking in large language models
Ryan Greenblatt, Carson Denison, Benjamin Wright +17
We present a demonstration of a large language model engaging in alignment faking: selectively complying with its training objective in training to prevent modification of its beha…
cs.LG2023★ 2 cited
Preventing Language Models From Hiding Their Reasoning
Fabien Roger, Ryan Greenblatt
Large language models (LLMs) often benefit from intermediate steps of reasoning to generate answers to complex problems. When these intermediate steps of reasoning are used to moni…
cs.LG2023
Benchmarks for Detecting Measurement Tampering
Fabien Roger, Ryan Greenblatt, Max Nadeau +2
When training powerful AI systems to perform complex tasks, it may be challenging to provide training signals which are robust to optimization. One concern is \textit{measurement t…