1 июн. 2019 г. · We show for the first time that it is possible to jointly learn the retriever and reader from question-answer string pairs and without any IR system.

1 нояб. 2016 г. · In this work, we introduce the first Open-. Retrieval Question Answering system (ORQA). ORQA learns to retrieve evidence from an open corpus, ...

Following the retrieval, the system engages a reading component, which is tasked with extracting or generating the answer from the selected passages.

1 июн. 2019 г. · This paper introduces a novel approach that iteratively improves over a weak retriever by alternately finding evidence from the up-to-date model.

11 сент. 2024 г. · We show for the first time that it is possible to jointly learn the retriever and reader from question-answer string pairs and without any IR ...

Recent work on open domain question answering (QA) assumes strong supervision of the supporting evidence and/or assumes a blackbox information retrieval ...

This document summarizes a research paper that introduces a new approach called Open-Retrieval Question Answering (ORQA) which can jointly learn to retrieve ...

6 авг. 2021 г. · Bibliographic details on Latent Retrieval for Weakly Supervised Open Domain Question Answering.

Продолжительность: 22:25
Опубликовано: 29 янв. 2022 г.

EMNLP 2018. Latent Retrieval for Weakly Supervised Open Domain Question Answering. Kenton Lee, Ming-Wei Chang, Kristina Toutanova. ACL 2019.