3 papers
cs.LG2025
SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms
Alex Havrilla, Edward Hughes, Mikayel Samvelyan +1
Large language model (LLM) driven synthetic data generation has emerged as a powerful method for improving model reasoning capabilities. However, most methods either distill large…
cs.CL2025
Neural Contextual Reinforcement Framework for Logical Structure Language Generation
Marcus Irvin, William Cooper, Edward Hughes +2
The Neural Contextual Reinforcement Framework introduces an innovative approach to enhancing the logical coherence and structural consistency of text generated by large language mo…
cs.MA2024
Cultural Evolution of Cooperation among LLM Agents
Aron Vallinder, Edward Hughes
Large language models (LLMs) provide a compelling foundation for building generally-capable AI agents. These agents may soon be deployed at scale in the real world, representing th…