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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…