Adaptive fine-tuning of LLMs with QLoRA adapters for enhanced understanding in cooperative multi-agent scenarios

This work explores fine-tuning of Large Language Models (LLMs) using QLoRA adapters to enhance performance in cooperative multi-agent scenarios. Using the Melting Pot framework and integrating multiple indicators of collective welfare and agent comprehension into a unified signal, the approach optim...