565 citations · 647 across the 8 of their papers we have counts for
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cs.LG2023★ 6 cited
The Alignment Problem in Context
Raphaël Millière
A core challenge in the development of increasingly capable AI systems is to make them safe and reliable by ensuring their behaviour is consistent with human values. This challenge…
cs.CL2023★ 1 cited
Decoding In-Context Learning: Neuroscience-inspired Analysis of Representations in Large Language Models
Safoora Yousefi, Leo Betthauser, Hosein Hasanbeig +2
Large language models (LLMs) exhibit remarkable performance improvement through in-context learning (ICL) by leveraging task-specific examples in the input. However, the mechanisms…
cs.CL2023★ 42 cited
The Vector Grounding Problem
Dimitri Coelho Mollo, Raphaël Millière
Large language models (LLMs) produce seemingly meaningful outputs, yet they are trained on text alone without direct interaction with the world. This leads to a modern variant of t…