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logprobs

AI, ML & GenAI interview questions tagged logprobs, across every topic.

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Concepts behind "logprobs"

The curriculum that explains the ideas these questions test.

Core
🧠 Foundations of LLMs & GenAISign in
Logits, Log-Probs, and Logit BiasThe output layer of an LLM is an API surface, not just an implementation detail. Logits are raw per-token scores, softmax turns them into probabilities, and log-probs are what providers actually return because they are numerically stable and add up across a sequence. Four production techniques live here: confidence scoring for routing and abstention, logit bias to ban or force a token, structured decoding by masking invalid tokens, and classification by reading a single position's log-probs instead of parsing prose. AI, ML, and GenAI engineer interviews probe it because it is the difference between treating the model as a text box and treating it as a probabilistic component.
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