32 citations · 38 across the 3 of their papers we have counts for
3 papers
GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning
Lakshya A Agrawal, Shangyin Tan, Dilara Soylu +14
Large language models (LLMs) are increasingly adapted to downstream tasks via reinforcement learning (RL) methods like Group Relative Policy Optimization (GRPO), which often requir…
Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs
Krista Opsahl-Ong, Michael J Ryan, Josh Purtell +4
Language Model Programs, i.e. sophisticated pipelines of modular language model (LM) calls, are increasingly advancing NLP tasks, but they require crafting prompts that are jointly…
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings
Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo +14
Diagnosing and mitigating changes in model fairness under distribution shift is an important component of the safe deployment of machine learning in healthcare settings. Importantl…