Ipon Passage igbapada adanwo

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

1. How does Dense Passage Retrieval decide which passages match a query?
   • Ṣe afiwe awọn aṣoju iponju ti awọn ibeere ati awọn ọrọ nipasẹ ibajọra
   • Kika iye awọn ọrọ ibeere ti o han ninu iwe-ipamọ kọọkan
   • Itumọ ibeere naa si SQL ṣaaju wiwa
   • Awọn iwe aṣẹ ipo nikan nipasẹ bii laipe wọn ti ṣe atẹjade
2. DPR nlo faaji 'bi-encoder' kan. Kí ni ìyẹn túmọ̀ sí?
   • O ṣe koodu koodu lẹmeji ati aropin awọn abajade
   • O ṣiṣẹ nikan lori awọn iwe aṣẹ bilingual
   • O ṣe koodu awọn kikọ mejeeji ati awọn ọrọ nigbakanna
   • O nlo awọn koodu koodu lọtọ meji, ọkan fun awọn ibeere ati ọkan fun awọn aye
3. Kilode ti a le ṣe iṣiro awọn olutọpa aye ni ilosiwaju ni DPR?
   • Nitoripe awọn ọrọ ko yipada ni kete ti kikọ
   • Nitoripe koodu koodu ibeere jẹ alaabo ni akoko wiwa
   • Nitoripe ọna kọọkan jẹ koodu ni ominira ti eyikeyi ibeere
   • Nitoripe awọn ọna ti wa ni ipamọ bi ọrọ aise nikan
4. Ẹtan ikẹkọ wo ni o jẹ ki DPR ṣe agbekalẹ ọpọlọpọ awọn apẹẹrẹ odi ni olowo poku?
   • Iyipada aami ID
   • Awọn odi-ipele, ni lilo awọn ọrọ miiran ni ipele kanna
   • Sisọ idaji awọn neuronu silẹ
   • Iforukọsilẹ pẹlu ọwọ gbogbo aye ti ko tọ
5. For what vocabulary mismatch can learned DPR representations be useful compared with lexical matching alone?
   • The passage is unrelated but repeats the query's terms
   • Every query contains only an exact serial number
   • The encoder is guaranteed to retrieve the right answer for all inputs
   • A relevant passage expresses a query's idea using different words
6. Ohun elo wo ni a nlo nigbagbogbo lati jẹ ki wiwa DPR agbegbe ti o sunmọ julọ ni iyara ni iwọn?
   • Atọka-aladugbo isunmọ bi FAISS
   • Iru iwe kaunti kan
   • A deede ikosile engine
   • A ti ibatan database da
7. Why can BM25-retrieved nonanswer passages be useful hard negatives when training DPR?
   • They guarantee that every retrieved passage is irrelevant
   • Their lexical overlap can make them challenging distractors that the retriever must distinguish from the answer passage
   • They remove the need for a positive answer passage
   • They force the passage encoder to count words without learning
8. After changing DPR's passage encoder, what should happen to a stored passage-vector index?
   • Keep the old embeddings because encoder weights cannot affect vectors
   • Rename the index without recalculating any representation
   • Recompute the passage embeddings with the intended compatible encoder and update the index
   • Disable the query encoder and search raw filenames instead