1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2026
Do LLMs Choose Like Humans? Using Cognitive Theory to Evaluate LLM Decision-Making
Johnathan Sun, Andrei Shleifer, Yonatan Belinkov
Large language models (LLMs) exhibit a range of human-like decision-making behaviors, but whether these reflect similar underlying mechanisms or surface-level mimicry remains uncle…
cs.AI2026
Persona Vectors in Games: Measuring and Steering Strategies via Activation Vectors
Johnathan Sun, Andrew Zhang
Large language models (LLMs) are increasingly deployed as autonomous decision-makers in strategic settings, yet we have limited tools for understanding their high-level behavioral…
cs.AI2025★ 1 cited
Does visualization help AI understand data?
Victoria R. Li, Johnathan Sun, Martin Wattenberg
Charts and graphs help people analyze data, but can they also be useful to AI systems? To investigate this question, we perform a series of experiments with two commercial vision-l…