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Kuis Perhatian Jendela Geser
Tinjau masker perhatian lokal dan penskalaan jendela tetap, dengan bidang reseptif bertumpuk, cache bergulir, lapisan Gemma 2, dan token global Longformer.
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With fixed window W, how does the pairwise attention term N times W scale as sequence length N increases?
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- With fixed window W, how does the pairwise attention term N times W scale as sequence length N increases?
- Quadratically in N despite W being fixed
- Exponentially in the vocabulary size by definition
- It never changes as any tokens are added
- Linearly in N
- How can stacked local attention layers propagate information beyond one layer’s direct neighborhood?
- By guaranteeing perfect recall of every earlier token
- Through intermediate representations passed across successive layers
- By randomly moving the original input’s coordinates
- By eliminating the need for all learned weights
- For a purely local causal attention layer, why can cache policy discard keys older than its active window?
- Those keys are outside that layer’s allowed direct attention links
- Every model layer must therefore have an identical whole-model memory bound
- Older tokens are always irrelevant to every possible task
- The model’s original weights have been deleted
- What attention pattern does the Gemma 2 report describe across its layers?
- Only one permanently disconnected input token
- No positional or attention computation anywhere
- Alternating local sliding-window and global attention
- A mandatory single identical local neighborhood for all models
- Untuk jendela geser kausal berukuran W, kunci manakah yang dapat ditanyakan pada posisi saya?
- Semua posisi masa depan setelah i
- Posisi i dikurangi W ditambah 1 sampai i
- Hanya posisi 0
- Subset acak dari semua posisi
- In the Mistral report’s rolling cache, which slot stores the keys and values for timestep i with buffer size W?
- A new permanent slot numbered i+W with no reuse
- Only slot zero for every timestep
- The slot at i modulo W
- A slot chosen by the output token’s alphabetical order
- Which context_len value is listed in the original Mistral 7B architecture table, separate from its larger theoretical stacked attention span?
- 4096 tokens
- 131072 tokens
- 32 tokens
- 8192 tokens
- In Longformer’s stated symmetric global-attention design, how does a selected global token connect to other sequence tokens?
- It attends to them and they can attend to it
- It can receive no attention from any other token
- It must ignore every token outside its local window
- It requires all non-global tokens to be deleted