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ChatGPT 및 LLM 퀴즈

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관련 가이드 경로ChatGPT와 LLM
질문 1 의 8

자기회귀 언어 모델의 일반적인 학습 목표는 무엇입니까?

모든 질문 미리보기8 질문

퀴즈를 풀면 정답과 설명이 나타납니다.

  1. 자기회귀 언어 모델의 일반적인 학습 목표는 무엇입니까?
    • 모든 답변을 실시간 검증된 데이터베이스에서 조회합니다
    • 이전 컨텍스트에서 가능한 다음 토큰을 예측합니다
    • 각 문장을 참 또는 거짓으로 분류합니다
    • 모든 입력을 컴퓨터 코드로 번역합니다
  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