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Register a new userR2-D2: A Modular Baseline for Open-Domain Question Answering
R2-D2: خط الأساس المعياري للسؤال المفتوح
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يعرض هذا العمل رواية خط أنابيب QA مفتوحة من أربعة مراحل R2-D2 (رتبة مرتين، اقرأ مرتين).يتكون خط الأنابيب من المسترد والمرور Reranker وقارئ استخراجي وقارئ عام وآلية تعزز التنبؤ النهائي من جميع مكونات النظام.نوضح قوتها عبر ثلاث مجموعات بيانات QA المجال المفتوحةيوضح تحليلنا على ما يلي: (1) الجمع بين القارئ الاستخراجي والمؤدي يحقق تحسينات مطلقة تصل إلى 5 مباراة محددة، وعلى الأقل ضعف كفاءة مثل الفرع الخلفي من نفس النماذج مع معلمات مختلفة، (2) القارئ الاستخراجي مع أقليمكن للممعلمات مطابقة أداء قارئ التوليد في مجموعات بيانات QA الاستخراجية.
This work presents a novel four-stage open-domain QA pipeline R2-D2 (Rank twice, reaD twice). The pipeline is composed of a retriever, passage reranker, extractive reader, generative reader and a mechanism that aggregates the final prediction from all system's components. We demonstrate its strength across three open-domain QA datasets: NaturalQuestions, TriviaQA and EfficientQA, surpassing state-of-the-art on the first two. Our analysis demonstrates that: (i) combining extractive and generative reader yields absolute improvements up to 5 exact match and it is at least twice as effective as the posterior averaging ensemble of the same models with different parameters, (ii) the extractive reader with fewer parameters can match the performance of the generative reader on extractive QA datasets.
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