36 citations · 56 across the 18 of their papers we have counts for
19 papers
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…
Efficient Pre-Training of LLMs through Truncated SVD Representations
Kaivan Kamali, Kajetan Schweighofer, Hormoz Shahrzad +3
LLM pretraining is extremely costly; therefore, parameter-efficient LLM architectures have recently emerged as a compelling research direction. One such promising approach is to re…
TerraLingua: Emergence and Analysis of Open-endedness in LLM Ecologies
Giuseppe Paolo, Jamieson Warner, Hormoz Shahrzad +3
As autonomous agents increasingly operate in real-world digital ecosystems, understanding how they coordinate, form institutions, and accumulate shared culture becomes both a scien…
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…
Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
Xin Qiu, Yulu Gan, Conor F. Hayes +6
Fine-tuning large language models (LLMs) for downstream tasks is an essential stage of modern AI deployment. Reinforcement learning (RL) has emerged as the dominant fine-tuning par…
Unlocking the Potential of Global Human Expertise
Elliot Meyerson, Olivier Francon, Darren Sargent +2
Solving societal problems on a global scale requires the collection and processing of ideas and methods from diverse sets of international experts. As the number and diversity of h…