LLM Inference Interview Questions, issue 21, Aug 21, 2026

The Search Error Trap

Senior ML Engineer interview at Google DeepMind, and the interviewer asks:

Your colleague says greedy decoding is a fine approximation of the most likely sequence, because we take the max at every step. Where does that argument break, and does beam search actually fix it?

Don’t say: Greedy is fine, beam search finds the highest-probability sequence.

Why your decoder is quietly throwing away the model's correct answers, and the counterintuitive reality of why reducing search error actively degrades user experience.

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