3 papers
cs.AI2026
To Whom Do Language Models Align? Measuring Principal Hierarchies Under High-Stakes Competing Demands
Fangyi Yu, Nabeel Seedat, Jonathan Richard Schwarz +1
Language models deployed in high-stakes professional settings face conflicting demands from users, institutional authorities, and professional norms. How models act when these dema…
cs.CL2025
Beyond Pointwise Scores: Decomposed Criteria-Based Evaluation of LLM Responses
Fangyi Yu, Nabeel Seedat, Dasha Herrmannova +2
Evaluating long-form answers in high-stakes domains such as law or medicine remains a fundamental challenge. Standard metrics like BLEU and ROUGE fail to capture semantic correctne…
cs.AI2025
When AIs Judge AIs: The Rise of Agent-as-a-Judge Evaluation for LLMs
Fangyi Yu
As large language models (LLMs) grow in capability and autonomy, evaluating their outputs-especially in open-ended and complex tasks-has become a critical bottleneck. A new paradig…