72 citations · 116 across the 17 of their papers we have counts for
3 papers · 1 filter
Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models
Laura Ruis, Maximilian Mozes, Juhan Bae +7
The capabilities and limitations of Large Language Models have been sketched out in great detail in recent years, providing an intriguing yet conflicting picture. On the one hand,…
Towards Reliable Evaluation of Behavior Steering Interventions in LLMs
Itamar Pres, Laura Ruis, Ekdeep Singh Lubana +1
Representation engineering methods have recently shown promise for enabling efficient steering of model behavior. However, evaluation pipelines for these methods have primarily rel…
Debating with More Persuasive LLMs Leads to More Truthful Answers
Akbir Khan, John Hughes, Dan Valentine +7
Common methods for aligning large language models (LLMs) with desired behaviour heavily rely on human-labelled data. However, as models grow increasingly sophisticated, they will s…