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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

R3: Reinforced Ranker-Reader for Open-Domain Question Answering

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Shuohang Wang

Singapore Management University


Mo Yu

IBM Research AI


Xiaoxiao Guo

IBM Research AI


Zhiguo Wang

IBM Research AI


Tim Klinger

IBM Research AI


Wei Zhang

IBM Research AI


Shiyu Chang

IBM Research AI


Gerry Tesauro

IBM Research AI


Bowen Zhou

JD.COM


Jing Jiang

Singapore Management University


DOI:

10.1609/aaai.v32i1.12053


Abstract:

In recent years researchers have achieved considerable success applying neural network methods to question answering (QA). These approaches have achieved state of the art results in simplified closed-domain settings such as the SQuAD (Rajpurkar et al. 2016) dataset, which provides a pre-selected passage, from which the answer to a given question may be extracted. More recently, researchers have begun to tackle open-domain QA, in which the model is given a question and access to a large corpus (e.g., wikipedia) instead of a pre-selected passage (Chen et al. 2017a). This setting is more complex as it requires large-scale search for relevant passages by an information retrieval component, combined with a reading comprehension model that “reads” the passages to generate an answer to the question. Performance in this setting lags well behind closed-domain performance. In this paper, we present a novel open-domain QA system called Reinforced Ranker-Reader (R3), based on two algorithmic innovations. First, we propose a new pipeline for open-domain QA with a Ranker component, which learns to rank retrieved passages in terms of likelihood of extracting the ground-truth answer to a given question. Second, we propose a novel method that jointly trains the Ranker along with an answer-extraction Reader model, based on reinforcement learning. We report extensive experimental results showing that our method significantly improves on the state of the art for multiple open-domain QA datasets.

Topics: AAAI

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HOW TO CITE:

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang R3: Reinforced Ranker-Reader for Open-Domain Question Answering Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang R3: Reinforced Ranker-Reader for Open-Domain Question Answering AAAI 2018, .

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang (2018). R3: Reinforced Ranker-Reader for Open-Domain Question Answering. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang. R3: Reinforced Ranker-Reader for Open-Domain Question Answering. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang. 2018. R3: Reinforced Ranker-Reader for Open-Domain Question Answering. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang. (2018) "R3: Reinforced Ranker-Reader for Open-Domain Question Answering", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang, "R3: Reinforced Ranker-Reader for Open-Domain Question Answering", AAAI, p., 2018.

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang. "R3: Reinforced Ranker-Reader for Open-Domain Question Answering". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang. "R3: Reinforced Ranker-Reader for Open-Domain Question Answering". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Shuohang Wang||Mo Yu||Xiaoxiao Guo||Zhiguo Wang||Tim Klinger||Wei Zhang||Shiyu Chang||Gerry Tesauro||Bowen Zhou||Jing Jiang. R3: Reinforced Ranker-Reader for Open-Domain Question Answering. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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