Kuiz Pembenaman Teks

Jawapan dan penjelasan muncul semasa anda mengambil kuiz.

1. What does a text embedding supply for a language comparison task?
   • A required spoken audio recording
   • A verbatim dictionary entry for every coordinate
   • A numerical vector representation of text
   • Only a grammar-repair instruction
2. In a representation trained to capture synonym similarity, what relationship is desirable for happy and joyful?
   • A relatively high similarity under the chosen scoring method
   • A mandatory identical vector for every word
   • A guarantee they are synonyms in every possible context
   • A requirement that neither word can be encoded
3. Apakah had utama pembenaman perkataan awal seperti Word2Vec dan GloVe?
   • Mereka tidak boleh disimpan pada komputer
   • Mereka hanya bekerja untuk imej
   • Mereka tidak memerlukan data latihan
   • Setiap perkataan mempunyai satu vektor tetap tanpa mengira konteks, jadi 'bank' bermaksud perkara yang sama di mana-mana sahaja
4. Bagaimanakah benam kontekstual moden menambah baik pada benam perkataan statik?
   • Mereka mengalih keluar semua nombor daripada perwakilan
   • Mereka memberikan perkataan vektor yang berbeza bergantung pada ayat sekelilingnya
   • Mereka hanya membenamkan huruf pertama setiap perkataan
   • Mereka menjadikan setiap vektor perkataan sama
5. Which documented default similarity method does Sentence Transformers use for embedding comparison?
   • Persamaan kosinus
   • Alphabetical order
   • Document creation date
   • Character count alone
6. What role can compatible text vectors play in a dense-retrieval RAG pipeline?
   • Guaranteeing every generated claim is correct
   • Eliminating the source corpus
   • Ranking candidate passages before they are supplied as context
   • Training a new language model on every query
7. Which pooling strategy is the stated default in the original Sentence-BERT paper?
   • A mandatory maximum over every possible vocabulary item
   • Mean pooling of output token vectors
   • Concatenation of all corpus documents
   • Randomly selecting an unchanged input byte
8. Which Sentence-BERT design allows stored sentences to be encoded before a new comparison sentence arrives?
   • Mandatory joint processing of every possible pair
   • Rebuilding encoder weights for each candidate
   • Encoding only the final comparison score
   • Independent sentence encoding through its siamese architecture