Explainable Causal Reinforcement Learning for heritage language revitalization programs for extreme data sparsity scenarios Introduction: A Personal Discovery in the Depths of Linguistic Data Scarcity It began during a late-night research session in my home lab, surrounded by stacks of annotated linguistic corpora and the soft hum of GPU clusters. I was exploring the intersection of reinforcement learning (RL) and causal inference for a project aimed at preserving endangered languages—what I call heritage language revitalization programs . The challenge was staggering: most heritage languages have fewer than 1,000 recorded utterances, often with no written grammar, no parallel corpora, and no native speakers left to consult. Traditional machine learning approaches fail catastrophically in such extreme data sparsity scenarios.…