Your question is Softmax in LLM Decoding. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain how you handle LLM decoding problems and decide when and how to use softmax.
Discuss the distinction between model logits, softmax probabilities, and token-selection strategies during autoregressive generation. Give a practical debugging and evaluation plan covering greedy decoding, sampling, temperature, top-k, top-p, repetition controls, numerical stability, and constrained or structured output. Explain when softmax should remain inside the model or inference runtime, when inspecting probabilities is useful, and how decoding choices affect quality, latency, and reproducibility.