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cs.CL2026
Environment-Grounded Automated Prompt Optimization for LLM Game Agents
Rean Clive Fernandes, Lukas Fehring, Theresa Eimer +2
LLM agents in interactive environments are highly sensitive to their prompts, yet prompt engineering remains a manual, task-specific process. We introduce an automated prompt optim…
cs.CL2025
promptolution: A Unified, Modular Framework for Prompt Optimization
Tom Zehle, Timo Heiß, Moritz Schlager +2
Prompt optimization has become crucial for enhancing the performance of large language models (LLMs) across a broad range of tasks. Although many research papers demonstrate its ef…
cs.CL2025
CAPO: Cost-Aware Prompt Optimization
Tom Zehle, Moritz Schlager, Timo Heiß +1
Large language models (LLMs) have revolutionized natural language processing by solving a wide range of tasks simply guided by a prompt. Yet their performance is highly sensitive t…