The token explosion paradox describes an AI phenomenon where generating more tokens per prompt reduces overall quality due to computational trade-offs. Used in model optimization, it helps engineers balance context length and coherence. Developers and researchers benefit by refining large language models for sharper, more efficient responses, avoiding performance degradation in extended conversations.
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