Home/Jonny Smith/Best Answers
  1. Asked: October 23, 2025In:

    Why does my language model generate repetitive loops?

    Jonny Smith
    Jonny Smith Begginer

    This happens when decoding is too greedy and the probability distribution collapses. The model finds one safe high-probability phrase and keeps choosing it. Using temperature scaling, top-k or nucleus sampling introduces controlled randomness so the model explores alternative paths. Common mistakes:Read more

    This happens when decoding is too greedy and the probability distribution collapses. The model finds one safe high-probability phrase and keeps choosing it.

    Using temperature scaling, top-k or nucleus sampling introduces controlled randomness so the model explores alternative paths.

    Common mistakes:

    • Using greedy decoding

    • No sampling strategy

    • Overconfident probability outputs

    The practical takeaway is that generation quality depends heavily on decoding strategy.

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  2. Asked: December 21, 2025In:

    Why does my chatbot answer confidently even when it is wrong?

    Jonny Smith
    Jonny Smith Begginer

    This happens because language models are trained to produce likely text, not to measure truth or confidence. They generate what sounds plausible based on training patterns. Since the model does not have a built-in uncertainty estimate, it always outputs the most probable sequence, even when that proRead more

    This happens because language models are trained to produce likely text, not to measure truth or confidence. They generate what sounds plausible based on training patterns.

    Since the model does not have a built-in uncertainty estimate, it always outputs the most probable sequence, even when that probability is low. This makes wrong answers sound just as confident as correct ones.

    Adding confidence estimation, retrieval-based grounding, or user-visible uncertainty thresholds helps reduce this risk.

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