Opsahl-Ong, Krista

Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Opsahl-Ong, K., Ryan, M. J., Purtell, J., Broman, D., Potts, C., Zaharia, M., & Khattab, O. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 212

Automating the Enterprise with Foundation Models

Wornow, M., Narayan, A., Opsahl-Ong, K., McIntyre, Q., Shah, N. H., & Re, C. (2024) · arXiv

Robotic Process Automation ApplicationsBusiness Process Modeling and Analysis

Cited by 15

Automating the Enterprise with Foundation Models

Wornow, M., Narayan, A., Opsahl-Ong, K., McIntyre, Q., Shah, N., & Ré, C. (2024) · Proceedings of the VLDB Endowment

Robotic Process Automation ApplicationsBusiness Process Modeling and Analysis

Cited by 15

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

Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Opsahl-Ong, K., Ryan, M. J., Purtell, J., Broman, D., Potts, C., Zaharia, M., & Khattab, O. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4

OfficeQA Pro: An Enterprise Benchmark for End-to-End Grounded Reasoning

Opsahl-Ong, K., Singhvi, A., Collins, J., Zhou, I., Wang, C., Baheti, A., Oertell, O., Portes, J., Havens, S., Elsen, E., et al. (2026) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0