Tag
The author speculates that LLMs trained on vast surveillance and social-media data could predict individual user behavior and deliver hyper-personalized persuasion at scale, raising concerns about autonomy, preference manipulation, and invisible discrimination.
DraftFM is a foundation model for predicting draft picks in Magic: The Gathering, enabling accurate day-zero drafting for new sets by leveraging card features and behavioral data. It demonstrated strong performance on held-out expansions and successfully forecasted an unreleased set.
A new process-level latent variable model (PLVM) predicts future behavioral strategies from partial process traces across tasks, demonstrated in PowerWash Simulator gameplay data.