3 papers
cs.AI2026
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…
cs.AI2026
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…
cs.AI2025
Adversarial Testing in LLMs: Insights into Decision-Making Vulnerabilities
Lili Zhang, Haomiaomiao Wang, Long Cheng +2
As Large Language Models (LLMs) become increasingly integrated into real-world decision-making systems, understanding their behavioural vulnerabilities remains a critical challenge…