fine-tuning-free

This paper investigates methods to steer Arabic LLMs toward dialect-specific generation by identifying sparse neuron populations and extracting dialect activation directions, enabling dialect control at inference time without fine-tuning.

DebiasRAG proposes a tuning-free, query-specific debiasing framework using retrieval-augmented generation to reduce social biases in LLMs without degrading their original capabilities.