32 citations · 38 across the 3 of their papers we have counts for
Showing cs.CLShow all
2 papers · 1 filter
cs.CL2025★ 2 cited
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…
cs.CL2024★ 4 cited
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…