Eugene Agichtein

LLMs are increasingly evaluated or trained using automated graders such as LLM-as-judges, but their scalar scores or preferences often provide little explanation of why an answer is good or bad. Rubric-based evaluation offers a more interpretable alternative by decomposing final scores into expli...

Evaluating retrieval-augmented generation (RAG) systems requires benchmarks that capture diverse question characteristics, yet practitioners lack empirical guidance on which dimensions to vary and at what granularity. We present HieraRAG, a hierarchical framework for studying granularity in RAG b...