A language model is in the process of generating the next word after the context 'The ocean is'. The model's entire vocabulary is limited to these five words: ['deep', 'blue', 'cold', 'vast', 'empty']. In the very first step of its decision-making process, the model must generate a list of all possible candidates for the next word. What does this initial list of candidates look like?

During the very first step of generating the next word for a given text, a language model produces a candidate list that includes every single token from its entire vocabulary.

A developer is troubleshooting a text generation system. They provide the input context 'The sun is shining and the sky is'. In the very first step of generating the next word, the system produces a candidate list containing only {'blue', 'clear', 'bright'}. The system's full vocabulary, however, contains over 10,000 words. Based on this observation, which fundamental principle of this initial generation stage has been incorrectly implemented?