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cs.AI2026
The Evolution Strategies Paradox: Better Models from Worse Perturbations
Roberto Dailey, Kajetan Schweighofer, Jamieson Warner +5
How is it possible for perturbation-based methods like Evolution Strategies (ES) to optimize billion-parameter large language models (LLMs)? Classical search methods are highly dep…
cs.AI2026
Beyond the Best Guess: Improving LLM Solution Coverage with Evolution Strategies
Conor F. Hayes, Elliot Meyerson, Kajetan Schweighofer +4
Large Language Models (LLMs) are increasingly deployed in discovery domains such as math and science. The usual approach is to present the problem to the model and use its answer a…
cs.AI2025
Solving a Million-Step LLM Task with Zero Errors
Elliot Meyerson, Giuseppe Paolo, Roberto Dailey +6
LLMs have achieved remarkable breakthroughs in reasoning, insights, and tool use, but chaining these abilities into extended processes at the scale of those routinely executed by h…