Maswali yanayounganishwa na mwongozo · Kati Kiwango

ChatGPT & Maswali ya LLM

Kagua kizazi cha ishara zinazofuata, tokeni, chatbot dhidi ya modeli, mafunzo dhidi ya kurejesha, na kwa nini majibu na manukuu fasaha bado yanahitaji ukaguzi wa chanzo.

Njia za mwongozo zinazohusianaChatGPT na LLM
Swali 1 ya 8

What is a common training objective for an autoregressive language model?

Hakiki kila swali8 maswali

Majibu na maelezo huonekana unapojibu maswali.

  1. What is a common training objective for an autoregressive language model?
    • Look up every answer in a live verified database
    • Predict a likely next token from the preceding context
    • Classify each sentence as true or false
    • Translate every input into computer code
  2. A language model can split one word into several processing units. What are those units?
    • Complete conversation turns
    • Tokens, which need not correspond to whole words
    • Final verified answers
    • Database records returned by retrieval
  3. How does a chatbot relate to an LLM?
    • A chatbot is an application that may combine a model with instructions, retrieval, tools, and an interface
    • A chatbot is always identical to one model
    • An LLM is the visual window in which a conversation appears
    • A chatbot is only a search index
  4. Which statement distinguishes training from prompting and retrieval?
    • A prompt necessarily changes model weights
    • Retrieval permanently modifies the model
    • A tool call is the same as a training epoch
    • Training adjusts parameters, while a prompt supplies current context and retrieval provides selected sources
  5. Does supplying sources eliminate hallucinations?
    • Yes, because every retrieved passage is always followed exactly
    • Yes, as long as the source is public
    • No; a model can misread, ignore, or miscite supplied evidence
    • No; retrieval prevents all useful answers
  6. What is a reliable way to check a factual claim with a citation?
    • Trust it if the title appears plausible
    • Open the cited source and confirm it supports the claim
    • Ask the same model whether the citation is real
    • Check only whether the URL loads
  7. A note says a workshop starts at 10:00 and registration closes Friday. What time does the workshop end?
    • The note does not state an ending time
    • 11:00
    • Noon
    • The time the chatbot was opened
  8. What does the original Transformer paper establish about every commercial chatbot?
    • That all products use an identical implementation
    • That every chatbot uses the same training data
    • That all models have the same context limit
    • It describes an architecture, but does not establish every product’s implementation details