ChatGPT ve Yüksek Lisans Sınavı

Testi çözdüğünüzde cevaplar ve açıklamalar görünür.

1. Otoregresif dil modeli için ortak eğitim hedefi nedir?
   • Her yanıtı canlı olarak doğrulanmış bir veritabanında arayın
   • Önceki bağlamdan olası bir sonraki jetonu tahmin edin
   • Her cümleyi doğru veya yanlış olarak sınıflandırın
   • Her girişi bilgisayar koduna çevirin
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