What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search (2026.findings-acl)
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| Challenge: | Recent work has demonstrated the promise of orchestrating large language models (LLMs) within evolutionary and agentic optimization systems. |
| Approach: | They present a large-scale study of LLM-guided evolutionary search . they find strong LLMs behave as local refiners, producing frequent improvements . weaker LLM optimizers exhibit large semantic drift, they say . |
| Outcome: | The results highlight the importance of trajectory analysis for understanding and improving LLM-based optimization systems. |
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