Context Window: How Much AI Can “Remember” at Once, and Why Your Information Gets Truncated
The context window is the maximum number of tokens a large language model can process at once, determining how much information AI can "see" when gene…
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Stop Conditions and Output Limits: How Generation Length Is Constrained
Scope note: This article explains the topic using public research and common engineering patterns. Retrieval, reranking, generation, and source-selec…
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Temperature and Top-P: Sampling Parameters Are Not Citation Preferences
Scope note: This article explains the topic using public research and common engineering patterns. Retrieval, reranking, generation, and source-selec…
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Top-P Sampling: A Dynamic Cumulative-Probability Candidate Set
Top-P sampling (also called nucleus sampling) dynamically filters candidates: AI accumulates probabilities from the highest-ranked tokens until the cu…
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Logits and Softmax: How AI Calculates the Probability of Each Next Word
Logits are the raw scores a model computes for each candidate token. The Softmax function converts these scores into a probability distribution (summi…
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