Jan 16
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Three questions to ace your next geni
interview. Final week question one.
Final week's topic, LLM evaluation.
Here's the question you need to be ready
for. How do you evaluate the quality of
retrieval in your rag pipeline? Here's
your expert answer. The quality of your
final answer depends almost entirely on
the quality of your retrieval. To
measure this retrieval, you create a
test set. Use metrics like precision at
the rate K to see if the top retrieved
documents are relevant and recall at the
rate K to see if you found the most
relevant documents you should have.
You're essentially checking if the
retriever is giving the LLM the right
information to succeed. If the retrieve
context is irrelevant or incomplete, the
LLM is set up to fail. Now, here's the
pro tip. mention that building this test
set manually is slow. A more scalable
advanced approach is using LLM as a
judge. This is where you use a powerful
model to programmatically score the
relevance of the retrieved documents for
each query. It's faster than humans and
shows you understand modern automated
evaluated pipelines.
In this video, we break down how to evaluate RAG retrieval quality step by step using real-world metrics like Precision@k, Recall@k, Hit Rate, MRR, and nDCG so you can see whether your retriever is actually pulling the right documents for your LLM. You will learn practical ideas like context relevance, contextual precision/recall, and how to combine retrieval metrics with answer-level checks such as faithfulness and groundedness to detect hallucinations early. Perfect for ML engineers, data scientists, and backend devs building RAG pipelines with vector databases, this session gives you a clear evaluation checklist and metric intuition you can directly plug into your experimentation framework. Get all important links here: 🔗 Get 1:1 Mentorship, Career Counselling, Mock Interviews, Mentorship from MAANG Professionals only with GfG Connect- Book your Session with an Expert Today: https://gfgcdn.com/tu/W7z/ Explore GfG Connect feed and join the fun: https://gfgcdn.com/tu/W80/ Visit website: https://geeksforgeeks.org/ Explore Premium LIVE, Online & Offline Courses (For maximum discount use code - GFGYT30) : https://geeksforgeeks.org/courses/ Solve POTD: https://www.geeksforgeeks.org/problem-of-the-day Ongoing contests, hackathons and events: https://www.geeksforgeeks.org/events Follow us for more fun, knowledge and resources, join us on our social handles: 📱Take GeeksforGeeks everywhere in your pockets! Don't forget to download our official app: https://geeksforgeeksapp.page.link/gfg-app 💬 X- https://x.com/geeksforgeeks 🧑💼 LinkedIn- https://www.linkedin.com/company/geeksforgeeks 📷 Instagram- https://www.instagram.com/geeks_for_geeks/?hl=en 💌 Telegram- https://t.me/s/geeksforgeeks_official 📌 Pinterest: https://in.pinterest.com/geeks_for_geeks/ Also, Subscribe if you haven't already! :) #RAG #RetrievalAugmentedGeneration #LLM #VectorDatabase #MLOps #GenAI #AIEngineering #InformationRetrieval #MRR #nDCG #Shorts #GfG