Induction Misoro muTransformers Quiz

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

1. Ndeupi mutemo unoshandiswa nemusoro weinduction?
   • Kufanotaura chiratidzo chinowanzoitika mumutauro
   • Gara uchikopa chiratidzo chekare chisina kuchinjwa
   • Kanganisa maratidziro echinyorwa
   • Wona [A] [B] kare, uye pa [A] zvakare kufanotaura [B]
2. What capability was linked to induction-head behavior in the cited 2022 study?
   • In-context learning in the examined models, with broader large-model claims framed as hypotheses
   • A proof that every form of reasoning uses only one identical circuit
   • Changing the tokenizer vocabulary during every prompt
   • Permanent weight updates whenever a repeated token appears
3. Ndeipi basa rinoitwa ne'previous-token head' mudunhu reinduction?
   • Inogadzira iyo yekupedzisira softmax
   • Inobvisa ruzivo rwenzvimbo
   • Inokopa ruzivo rwekutanga kwechiratidzo chemberi kuitira kuti kuenzanirana kuitike
   • Inoita normalizes kutarisisa huremu
4. Mangani misoro yekutarisisa inowanzobatanidzwa mune canonical induction wedunhu?
   • Imwe chete
   • Maviri, akaumbwa kumativi ose
   • Mazana muchikamu chimwe chete
   • Zero; ndeye feed-forward chete
5. What training relationship did the induction-head study report in the models it examined?
   • Head formation coincided with changes in loss behavior and increased in-context learning
   • All heads were fully formed before any training
   • Induction behavior could only appear after every parameter was frozen forever
   • The same exact training transition must occur in every future model
6. Ibasa ripi raizoitwa nemusoro weinduction zvakanyanya?
   • Kugadzira chiyero chenhamba
   • Kudzvinyirira zviyero zvemuenzaniso
   • Kuvharidzira chirevo chekuisa
   • Kudzokorodza nhevedzano nekukopa izvo zvakatevera kufananidzira tokeni
7. What roles do query-key matching and the output-value path play in the canonical induction circuit?
   • Query-key computations generate the final text filename; output-value computations train the tokenizer
   • Query-key computations select the matching context position; output-value computations promote the token information there
   • Both paths only count the total number of context words
   • The output-value path selects a position without any attention pattern
8. Does a demonstrated two-head induction circuit prove that every large-model in-context task uses that mechanism alone?
   • Yes; every architecture and prompt has already been causally tested
   • Yes; no other network computation can influence a prediction
   • No; the wider explanation remains a hypothesis needing model- and task-specific evidence
   • Only the number of parameters determines whether the proof is universal