25 LLM Foundation Interview Questions: From Tokens to Scaling Laws
techNmak · x · 2026-08-16
techNmak shares a curated list of 25 LLM foundation interview questions covering core mechanics (input to output token, autoregressive modeling, logits/softmax), decoding & training objectives (greedy decoding, temperature, top-k/top-p, cross-entropy, perplexity), tokenization (BPE, WordPiece, SentencePiece, special tokens), context & representations (embeddings, context window, Lost in the Middle), prompting & architectures (few-shot, in-context learning, encoder/decoder), and scaling & failure modes (parameter count, neural scaling laws, Chinchilla, data quality, memorization vs generalization). Each answer is grounded in actual papers.
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