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20242026
most citedLanguage Models Trained to do Arithmetic Predict Human Risky and Intertemporal Choice

2 citations · 2 across the 6 of their papers we have counts for

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cs.CL2025

Steering Risk Preferences in Large Language Models by Aligning Behavioral and Neural Representations

Jian-Qiao Zhu, Haijiang Yan, Thomas L. Griffiths

Changing the behavior of large language models (LLMs) can be as straightforward as editing the Transformer's residual streams using appropriately constructed "steering vectors." Th…

cs.CL2025

Recovering Event Probabilities from Large Language Model Embeddings via Axiomatic Constraints

Jian-Qiao Zhu, Haijiang Yan, Thomas L. Griffiths

Rational decision-making under uncertainty requires coherent degrees of belief in events. However, event probabilities generated by Large Language Models (LLMs) have been shown to…