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Attention and Context: What the Model Can Use
Today
1. Inside a Language Model · 3 of 4
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Next
Orient
Fitting evidence is not the same as using evidence
Turn a 16K limit into an evidence budget
Predict
Run a long-context evidence-use experiment
Close
Practice
Related
Attention and Context: What the Model Can Use
Intermediate
☆
📑
Capacity is not recall, and a long window is not a database
Orient
Fitting evidence is not the same as using evidence
Turn a 16K limit into an evidence budget
Predict
Run a long-context evidence-use experiment
Close
Practice
Related
Practice activities and scenarios are optional. Mark the lesson complete after reading, and return to practice whenever it helps.
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07
Optional practice
🧠 Optional scenario practice
Q1
A 200-page manual fits inside a model’s documented input limit, but answers about buried clauses are unreliable. What should the team test first?
A
Move to the largest advertised window and assume usable recall rises in direct proportion to the new capacity
B
Place one known clause at the beginning, confirm that case works, and treat the positional workaround as a general solution
C
Retrieval and position-sensitive accuracy on representative clauses and distractors
D
Reserve a larger maximum output because giving the model more answer space should make buried input evidence easier to find
Q2
Which statement about attention is most accurate?
A
It is a learned computation that mixes token information; an attention score alone is not a faithful explanation of reasoning
B
The highest attention weight is a faithful causal explanation of why the model chose its final answer
C
Once a token fits inside the context window, attention makes it equally available regardless of position or surrounding distractors
D
Attention writes important conversation tokens into persistent storage so that later sessions can retrieve them without application memory
08
Up Next
Intermediate
Next-Token Generation: From Logits to a Response
Beginner
Message Roles and Instruction Priority
Intermediate
In-Context Learning: Instructions, Examples, and Ambiguity
📝 Notes
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Next: Next-Token Generation: From Logits to a Response →