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To manage decoding costs and prevent excessive verbosity in practical applications, a common stopping criterion is to impose a maximum output length. Under this rule, the text generation process is halted as soon as the model generates a predefined number of tokens.

Maximum Output Length as a Stopping Criterion

Imagine you are developing a system that uses a text-generating model to answer customer support questions. To ensure responses are concise and to manage processing time, you implement a single, strict rule: the model must stop generating text as soon as it has produced exactly 100 tokens. Critically evaluate this rule as the *sole* method for ending a response. Discuss one major benefit and two significant potential drawbacks of this approach from a user experience perspective.

Critique of a Fixed-Length Generation Rule

Based on the scenario described, which specific text generation rule should the developer implement to most directly and effectively prevent these overly long responses, and how does this rule function?

Controlling Chatbot Verbosity

A developer configures a language model for a customer support chatbot. To ensure responses are concise, they set the *only* stopping criterion to be a maximum output length of 30 tokens. Which of the following issues is most likely to occur as a direct result of this specific configuration?

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