Goals and Philosophy

With language models now commonly deployed within agentic systems and interactive applications, careful evaluation has become a central research need. Our group focuses on developing clear, reproducible methods for understanding model behavior across different tasks and contexts. We aim to characterize model strengths and limitations with rigor, grounding our work in empirical evidence rather than assumptions. Our philosophy is that progress in AI is best supported by transparent evaluation frameworks that inform development, guide responsible use, and help the community build models that are reliable, interpretable, and useful.