Résumé
Exposition bias mooy bërëb biy feeñ sudee ab model buñu tàggat ci prefix yu jaar yoon rek dafa wara, ci inference, condition ci ay output yu jaarul yoon. Échantillonnage buñ waajal prograamu njàngale la buy tëj bërëb boobu ndànk-ndànk.
Échantillonnage buñ waajal ak Exposition Bias, dafay am njeexital ci kalite model bi, njëgu infrastructure bi, latency bi, ak wóor gi ci echel bi.
Plongeur bu xóot
Model yiñ tàggat ak jàngalekat bi di forse, duñu musa gis dëgg-dëgg tokens ni contexte, waaye ci jamonoy generation ñu ngi feedback seen predictions. Su njuumte bu teel wàcce model bi ci anam wimu musul dajeel ci diiru tàggat yaram, njuumte yi mën nañu snowball, muy anam wu ñuy woowe exposition bias. Sampling buñ nara def, bi Bengio ak ay naataango dugal ci 2015, dafay saafara jafe-jafe yii ci flipping benn piyeesu xaalis ci jéego bu nekk ci decoding ci diiru tàggat: ak yenn probabilite dafay dundal token dëgg (jàngalekat bi di forse) te luko moy dafay dundal model bi boppam sampled prediction. Li mëna am ci jëfandikoo dëgg gi ci suuf mingi tàmbali ci wetu benn ba noppi di wàññeeku ci tàggat yaram jaaraleko ci benn kalendriye (ligneer, exponentiel, wala inverse-sigmoid), kon model bi dafay gëna dem ba génne boppam ba noppi jàng ni ñuy defaree ay njuumteem.
Gis-gis xarala
Ci jéego t, model bi dafay jël misaalu benn variable Bernoulli ak probabilite epsilon_i ngir tànn token wurus bi; epsilon_i dafay jeex lu tàggat bi di gëna dem. Benn ci mbir yu am solo yi mooy dundal ay token yuñ samplee dafay tax objectif bi nekk ci anam wu jaarul yoon, te sampling bu diskret bi mënul wuute, moo tax gradient yi duñu jaar bu baax ci feed-back token bi. Variante yi dañuy jëfandikoo Gumbel-softmax bu jub wala ay relaxation yuñ mëna wuutale ngir wàññi lii, ba noppi pexe yu toppalante yi dañuy gëna xéewale metric bu melni BLEU ci saasi.
Xam échantillonnage biñ nara def ak exposition bias
Exposition bias mooy bërëb biy feeñ sudee ab model buñu tàggat ci prefix yu jaar yoon rek dafa wara, ci inference, condition ci ay output yu jaarul yoon. Échantillonnage buñ waajal prograamu njàngale la buy tëj bërëb boobu ndànk-ndànk. Échantillonnage buñ waajal ak Exposition Bias, dafay am njeexital ci kalite model bi, njëgu infrastructure bi, latency bi, ak wóor gi ci echel bi. Ngir tabax xam-xam bu xóot, jàppal Scheduled Sampling ak Exposure Bias ni xeetu liggéey, du benn man-man: leeral njariñ yi nga bëgg, leeral xalaat yi, ak tàqale li sistem bi mëna def ci anam wu wóor ak li ba leegi soxla àtteb kàngam.
Ci jëf, ekip yu am doole yiy jëfandikoo échantillonnage buñ waajal ak Exposition Bias dañuy gëna baaxal architecture, done, ak tànneefi infrastructure ci wàllu wóor ak njëg. Dañuy bind kritër yu leer ngir am ndam, natt leen ci done yu dëggu ak def liggéey, ba noppi ñu baamtu ci anamu ñàkka mëna seetlu, du ci benn yoon benchmark wins. Mooy barab bi xam-xam theorie bi di soppiku nekk kàttan buy yàgg ci produit yi, ci politik yi ak ci liggéey yi.
Dogal yi architecture di jël dañuy indi njariñ ak njëgu liggéey bi ay at ci ginaaw. Ci jamano jooju, Optimisation benn benchmark mën na nëbb ñakk kattan yu gëna yaatu ci sistem bi. Xeetu jëf bi gëna dëgër mooy boole gaawaayu jàngat ak disipline nguur: doxal pilote, jàpp firnde, siiwal dogal yi, ak wéy di yeesal kaaraange gi ci anam wi ñuy doxalee, li jëfandikukat bi di xaar, ak sàrti sàrt yi di jëm kanam.
njeextalu pexe
Dogal yi architecture di jël dañuy indi njariñ ak njëgu liggéey bi ay at ci ginaaw.
Dogal yi architecture di jël dañuy indi njariñ ak njëgu liggéey bi ay at ci ginaaw. Ci jëfandikoo yu am kalite bu kawe, loolu dañu koy tekki ci sàrti liggéey yuñ mëna natt, ay peggu boroom, ak ay xew-xewu xoolaat yu bari suko defee ekip yi mëna yokk wóolu seen bopp ci barabu yokk lu jaxasoo.
Njàngalem xarala yi dafay jàppale ekip yi ñu tànn li gën, te baña yam ci li gëna bees daal.
Njàngalem xarala yi dafay jàppale ekip yi ñu tànn li gën, te baña yam ci li gëna bees daal. Ci jëfandikoo yu am kalite bu kawe, loolu dañu koy tekki ci sàrti liggéey yuñ mëna natt, ay peggu boroom, ak ay xew-xewu xoolaat yu bari suko defee ekip yi mëna yokk wóolu seen bopp ci barabu yokk lu jaxasoo.
Tanneef yu gëna baax ci wàllu ingeñër dina wàññi jafe-jafe yi ci wàllu wóor ci liggéey bi.
Tanneef yu gëna baax ci wàllu ingeñër dina wàññi jafe-jafe yi ci wàllu wóor ci liggéey bi. Ci jëfandikoo yu am kalite bu kawe, loolu dañu koy tekki ci sàrti liggéey yuñ mëna natt, ay peggu boroom, ak ay xew-xewu xoolaat yu bari suko defee ekip yi mëna yokk wóolu seen bopp ci barabu yokk lu jaxasoo.
Doxal ci àdduna dëgg
Taggat ab xeetu nataal-captioning ak sampling buñ waajal suko defee mu jàng wéyal bu baax ginaaw baat buñu wax lu jaarul yoon
Dafay yàq probabilite forse jàngalekat bi ak oraaru sigmoid bu dëddu ci sistemu tekki masin neuronal
Saytu ab chatbot buy dem ci ay boucles yu jaxasoo ni exposition-bias symptom bu juge ci forsu jàngalekat bu seer
Tegtale poñ yi BLEU am ci ab resuméer buñu tàggat ak jàngalekat bu mat sëkk ak benn buñu tàggat ci échantillonnage
Modèlu jëfandikoo
Sampling buñ waajal ak Exposition Bias ci jëf
Taggat ab xeetu nataal-captioning ak sampling buñ waajal suko defee mu jàng wéyal bu baax ginaaw ab baat buñu wax lu jaarul yoon.
Taggat benn xeetu nataal-captioning ak sampling buñ waajal suko defee mu jàng wéyal ci anam wu neex ginaaw benn baat buñu wax lu jaarul yoon. Ekip yi dañuy faral di am njariñ yu gëna baax suñu joxee threshold yu baax ci kanam, tëye yoonu escalation nit ngir jafe-jafe yi, ba noppi topp njariñu produit ak njëgu njuumte ci diir bi.
Sampling buñ waajal ak Exposition Bias ci jëf
Dakkal probabilite bi jàngalekat bi di forse ak oraaru sigmoid bu dëddu ci sistemu tekki masin neuronal.
Decaying jàngalekat-forcing probabilite ak benn oraire inverse-sigmoid ci sistemu tekki masin neural Ekip yi dañuy faral di am njariñ yu gëna baax suñu joxee threshold yu baax ci kanam, tëye yoonu escalation nit ngir jafe-jafe yi, ba noppi topp njariñu produit ak njëgu njuumte ci diir bi.
Sampling buñ waajal ak Exposition Bias ci jëf
Saytu ab chatbot buy dem ci ay bouclage yu jaxasoo ni exposition-bias symptom bu juge ci forsu jàngalekat bu seer.
Diagnostic chatbot buy dem ci loop yu jaarul yoon, muy màndarga exposition-bias bu juge ci jàngalekat bu sell biy forse. Ekip yi dañuy faral di am njariñ yu gëna baax suñu joxee threshold yu baax ci kanam, tëye yoonu escalation nit ngir jafe-jafe yi, ba noppi topp njariñu produit ak njëgu njuumte ci diir bi.
Sampling buñ waajal ak Exposition Bias ci jëf
Tegtale poñ yi BLEU am ci ab resumé buñu tàggat ak jàngalekat bu mat sëkk ak benn buñu tàggat ci sampling biñ nara def.
Tegtale poñ yi BLEU am ci ab summazer buñu tàggat ak jàngalekat bu mat te forse ak benn buñu tàggat ak sampling buñ nara def. Ekip yi dañuy faral di am njariñ yu gëna baax suñu joxee thresholds yu baax ci kanam, tëye yoonu escalation nit ngir jafe-jafe yi, ba noppi topp njariñu produit ak njëgu njuumte ci diir bi.
Risk yi ak balustrade yi
Optimize benn benchmark mën na nëbb ñakk kattan yu gëna yaatu ci sistem bi.
Njëg li ñuy fay ci infrastructure yi ak ci toppatoo dañuy faral di suufeel.
Bu sistem yi di gëna xawa jafee xam, jafe-jafe yi am ci wàllu kaaraange ak seetlu mën nañu gëna bari.
Roadmap ngir samp gi
Mandargal latency, kalite, ak njëg yi laata ngay jëfandikoo.
Mandargal latency, kalite, ak njëg yi laata ngay jëfandikoo. Japp jéego bu nekk ni buntu firnde: sudee mattul kritër yi, noppali génne gi, tëj bërëb bi, ba noppi nga yaatal jëfandikoo gi.
Benchmark ci biir sargal ak done yu dëggu.
Benchmark ci biir sargal ak done yu dëggu. Japp jéego bu nekk ni buntu firnde: sudee mattul kritër yi, noppali génne gi, tëj bërëb bi, ba noppi nga yaatal jëfandikoo gi.
Jumtukaay bi di saytu njuumte yi, derive bi ak njeextalu jëfandikukat bi.
Jumtukaay bi di saytu njuumte yi, derive bi ak njeextalu jëfandikukat bi. Japp jéego bu nekk ni buntu firnde: sudee mattul kritër yi, noppali génne gi, tëj bërëb bi, ba noppi nga yaatal jëfandikoo gi.
Waajal rollback ak yooni tontu ci jafe-jafe yi laata ngay eskale.
Waajal rollback ak yooni tontu ci jafe-jafe yi laata ngay eskale. Japp jéego bu nekk ni buntu firnde: sudee mattul kritër yi, noppali génne gi, tëj bërëb bi, ba noppi nga yaatal jëfandikoo gi.