565 citations · 773 across the 14 of their papers we have counts for
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cs.CL2025
HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation
Cristina Garbacea, Chenhao Tan
Alignment algorithms are widely used to align large language models (LLMs) to human users based on preference annotations. Typically these (often divergent) preferences are aggrega…
cs.AI2025★ 1 cited
Evaluating the Goal-Directedness of Large Language Models
Tom Everitt, Cristina Garbacea, Alexis Bellot +4
To what extent do LLMs use their capabilities towards their given goal? We take this as a measure of their goal-directedness. We evaluate goal-directedness on tasks that require in…