Kuis Verifikasi Pengambilan Sampel Spekulatif

Jawaban dan penjelasan muncul saat Anda mengikuti kuis.

1. Apa ide inti di balik pengambilan sampel spekulatif?
   • Gunakan model draf kecil untuk mengusulkan beberapa token yang diverifikasi oleh model besar secara paralel
   • Latih satu model raksasa untuk melewati lapisan secara dinamis
   • Simpan setiap kemungkinan kalimat terlebih dahulu
   • Ganti pengambilan sampel dengan decoding serakah untuk menghemat waktu
2. Mengapa pengambilan sampel spekulatif tidak menurunkan kualitas keluaran?
   • Karena rancangan modelnya selalu benar
   • Karena aturan verifikasi membuat distribusi akhir identik dengan target sampling murni
   • Karena ini hanya berfungsi pada perintah singkat
   • Karena ini merupakan rata-rata keluaran kedua model
3. In exact speculative sampling, what happens when a drafted token is rejected?
   • It outputs the rejected draft token unchanged
   • It discards the entire conversation and restarts
   • The algorithm samples from a corrected residual distribution at that position
   • It permanently changes the target model
4. Under exact speculative sampling, what is guaranteed about the output distribution?
   • It is always deterministic
   • It matches the draft model’s distribution instead
   • It is more diverse than every target-model output
   • It matches the target model’s sampling distribution
5. What information does the target verification pass provide in exact speculative sampling?
   • Target probabilities for proposed positions, used for acceptance tests and residual resampling
   • A guarantee that no target-model computation is needed
   • Only the draft model’s next-token distribution
   • A corrected token sequence without any sampling
6. Which description correctly distinguishes two self-speculative approaches?
   • Both use only an unrelated small draft model
   • Medusa adds prediction heads, while EAGLE uses feature-space proposals
   • Medusa is a tokenizer and EAGLE is a reward model
   • Both remove the target model from decoding
7. The draft assigns probability 0.8 to a token and the target assigns 0.4. What is the speculative acceptance probability?
   • 0,2
   • 0,4
   • 0,5
   • 1.0
8. What most limits speculative sampling’s realized speedup?
   • The color of the model’s interface
   • The target model’s name length
   • Whether the prompt contains punctuation
   • The draft-model cost and how much proposed work the target accepts