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Low-resource language models can get a major boost in translation quality and tokenization efficiency by using reinforcement learning to directly enforce structural constraints like sequence length and linguistic well-formedness during training.
Forget hand-crafted student profiles: HACHIMI generates a million theory-aligned, quota-controlled student personas, offering a standardized synthetic population for educational LLM benchmarking and social-science simulations.
