32 citations · 39 across the 6 of their papers we have counts for
6 papers
Comparative reversal learning reveals rigid adaptation in LLMs under non-stationary uncertainty
Haomiaomiao Wang, Tomás E Ward, Lili Zhang
Non-stationary environments require agents to revise previously learned action values when contingencies change. We treat large language models (LLMs) as sequential decision polici…
Rigidity in LLM Bandits with Implications for Human-AI Dyads
Haomiaomiao Wang, Tomás E Ward, Lili Zhang
We test whether LLMs show robust decision biases. Treating models as participants in two-arm bandits, we ran 20000 trials per condition across four decoding configurations. Under s…
Privacy-Aware Energy Consumption Modeling of Connected Battery Electric Vehicles using Federated Learning
Sen Yan, Hongyuan Fang, Ji Li +3
Battery Electric Vehicles (BEVs) are increasingly significant in modern cities due to their potential to reduce air pollution. Precise and real-time estimation of energy consumptio…
Adaptive data collection for intra-individual studies affected by adherence
Greta Monacelli, Lili Zhang, Winfried Schlee +3
Recently the use of mobile technologies in Ecological Momentary Assessments (EMA) and Interventions (EMI) has made it easier to collect data suitable for intra-individual variabili…
Generation of Synthetic Electronic Health Records Using a Federated GAN
John Weldon, Tomas Ward, Eoin Brophy
Sensitive medical data is often subject to strict usage constraints. In this paper, we trained a generative adversarial network (GAN) on real-world electronic health records (EHR).…
Predicting Injectable Medication Adherence via a Smart Sharps Bin and Machine Learning
Yingqi Gu, Akshay Zalkikar, Lara Kelly +2
Medication non-adherence is a widespread problem affecting over 50% of people who have chronic illness and need chronic treatment. Non-adherence exacerbates health risks and drives…