Ziems, Noah

Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Tasks

Szymanski, A., Ziems, N., Eicher-Miller, H. A., Li, T. J.-J., Jiang, M., & Metoyer, R. A. (2025) · Proceedings of the 30th International Conference on Intelligent User Interfaces

Artificial Intelligence in LawTopic Modeling

Cited by 77

Explaining Tree Model Decisions in Natural Language for Network Intrusion Detection

Ziems, N., Liu, G., Flanagan, J., & Jiang, M. (2023) · arXiv

Explainable Artificial Intelligence (XAI)Network Security and Intrusion Detection

Cited by 7

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Agrawal, L. A., Tan, S., Soylu, D., Ziems, N., Khare, R., Opsahl-Ong, K., Singhvi, A., Shandilya, H., Ryan, M. J., Jiang, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 7

BigCodeArena: Unveiling More Reliable Human Preferences in Code Generation via Execution

Zhuo, T. Y., Jin, X., Liu, H., Jiang, J., Liu, T., Gong, C., Bishnoi, B., Mishra, V., Suppa, M., Ziems, N., et al. (2025) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 0