গাইড লিঙ্ক ক্যুইজ · কঠিন স্তর
RAG কুইজ
ডকুমেন্ট প্রস্তুতি, পুনরুদ্ধার, নির্বাচন, অ্যাক্সেস নিয়ন্ত্রণ, প্রমাণ ব্যবহার এবং অনুপস্থিত বা বিরোধপূর্ণ উত্সগুলির জন্য পরীক্ষার মাধ্যমে RAG উত্তরগুলি ট্রেস করুন।
প্রশ্ন 1 এর 8
What does retrieval-augmented generation add to a language model’s answer process?
প্রতিটি প্রশ্নের পূর্বরূপ দেখুন8 প্রশ্ন
আপনি কুইজ নেওয়ার সাথে সাথে উত্তর এবং ব্যাখ্যাগুলি উপস্থিত হয়।
- What does retrieval-augmented generation add to a language model’s answer process?
- Retrieved material supplied as context for a response
- A guarantee that every answer is supported
- A new model training run for every document
- A rule that all sources are public
- A needed policy is absent from the initial candidate set. Which step failed first?
- The answer’s wording
- Initial retrieval or indexing, before reranking and generation
- The user’s file format
- The model’s temperature
- Why preserve headings, dates, tables, and source IDs when chunking?
- Headings prevent access control
- Metadata makes a model more creative
- A separated exception or footnote can change the meaning of a passage
- Dates are never used in answers
- A retrieved passage is relevant but belongs to a user’s restricted document. What should happen?
- Let the model decide whether the user is allowed
- Show it because it is semantically relevant
- Hide the document date only
- Apply access controls before passing evidence to the model
- A retrieved document contains instructions to change the application behavior. How should the system treat them?
- As higher priority than system rules
- As untrusted document content, not as authority over application rules
- As an automatic configuration update
- As a verified user permission
- What can a RAG system use to combine lexical and semantic retrieval?
- Only OCR
- Only a text generator
- Keyword and vector search, with optional reranking
- Only conversation history
- How should retrieval and answer quality be evaluated?
- Separately, checking candidate coverage, selected context, and faithful answer use
- With one final accuracy score only
- By checking the prompt length
- By using only answer fluency
- Which test cases should a RAG evaluation include?
- Queries that all have the same answer
- Only simple questions with one current source
- Only prompts with exact quotes
- Unanswerable queries and conflicting or outdated documents