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Efficient Passage Retrieval with Hashing for Open-domain Question Answering
2021
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
unpublished
Preserved Fulltext
Most state-of-the-art open-domain question answering systems use a neural retrieval model to encode passages into continuous vectors and extract them from a knowledge source. ...
Compared with DPR, BPR substantially reduces the memory cost from 65GB to 2GB without a loss of accuracy on two standard open-domain question answering benchmarks: Natural Questions and TriviaQA. ...
Acknowledgement We are grateful for the feedback and suggestions from the anonymous reviewers and the members of the UW NLP group. ...
doi:10.18653/v1/2021.acl-short.123
fatcat:xjp75dipubgjndc3p4nksfgsii
Open Domain Question Answering over Tables via Dense Retrieval
[article]
2021
arXiv
pre-print
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Recent advances in open-domain QA have led to strong models based on dense retrieval, but only focused on retrieving textual passages. ...
In this work, we tackle open-domain QA over tables for the first time, and show that retrieval can be improved by a retriever designed to handle tabular context. ...
This work was completed in partial fulfillment for the PhD degree of the first author, which was also supported by a Google PhD fellowship. ...
arXiv:2103.12011v2
fatcat:jwrtnmv4lbhflf425xqmddyjsi
ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction
[article]
2021
arXiv
pre-print
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In this work, we introduce ColBERTv2, a retriever that couples an aggressive residual compression mechanism with a denoised supervision strategy to simultaneously improve the quality and space footprint ...
Neural information retrieval (IR) has greatly advanced search and other knowledge-intensive language tasks. ...
As a further test of outof-domain generalization, we evaluate the strongest three models-ColBERTv2, SPLADEv2, and vanilla ColBERT-on retrieval for open-domain question answering, similar to the out-of-domain ...
arXiv:2112.01488v2
fatcat:vaucpjvuejbidiibss5pxgu7y4
Generative Retrieval for Long Sequences
[article]
2022
arXiv
pre-print
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Text retrieval is often formulated as mapping the query and the target items (e.g., passages) to the same vector space and finding the item whose embedding is closest to that of the query. ...
We also conjecture that generative retrieval is complementary to traditional retrieval, as we find that an ensemble of both outperforms homogeneous ensembles. ...
an open domain multi-hop question answering dataset, which requires aggregating multiple Wikipedia passages through logical reasoning or sequential processing. ...
arXiv:2204.13596v1
fatcat:i2uu5j4qbjhfpambxfdcun47k4
Cluster-Former: Clustering-based Sparse Transformer for Long-Range Dependency Encoding
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2009.06097v1 fatcat:jnkmaa2y6bf5neop4lq5ekrzgy
This new design allows information integration beyond local windows, which is especially beneficial for question answering (QA) tasks that rely on long-range dependencies. ...
However, despite its effectiveness in modeling short sequences, self-attention suffers when handling inputs with extreme long-range dependencies, as its complexity grows quadratically with respect to the ...
., 2017) : The goal of this task is to answer open-domain questions from Trivia Challenge. All the passages harvested through information retrieval can be used to answer questions. ...
arXiv:2009.06097v2
fatcat:stsmr7vwone2jfm3fo7t2t2dku
MFAQ: a Multilingual FAQ Dataset
[article]
2021
arXiv
pre-print
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We adopt a similar setup as Dense Passage Retrieval (DPR) and test various bi-encoders on this dataset. ...
Although this is significantly larger than existing FAQ retrieval datasets, it comes with its own challenges: duplication of content and uneven distribution of topics. ...
Dense passage retrieval for open-domain question answering. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769-6781, Online. ...
arXiv:2109.12870v2
fatcat:okrggnbm4zepvnrw3uqsd2oroi
Knowledge-Aided Open-Domain Question Answering
[article]
2020
arXiv
pre-print
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, there is still much room for improving open-domain QA systems since document retrieval and answer reranking are still unsatisfactory. ...
Open-domain question answering (QA) aims to find the answer to a question from a large collection of documents.Though many models for single-document machine comprehension have achieved strong performance ...
We first fine-tune the reader (with only L 2 ) for 1 epoch, and then fine-tune the whole model (with L) for another 2 epoches. ...
arXiv:2006.05244v1
fatcat:jalykeljibcbdeatk2muvkghu4
XLMRQA: Open-Domain Question Answering on Vietnamese Wikipedia-based Textual Knowledge Source
[article]
2022
arXiv
pre-print
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A reader-based QA system is a high-level search engine that can find correct answers to queries or questions in open-domain or domain-specific texts using machine reading comprehension (MRC) techniques ...
Question answering (QA) is a natural language understanding task within the fields of information retrieval and information extraction that has attracted much attention from the computational linguistics ...
Conclusion and Future Work In this paper, we introduced XLMRQA, a QA system based on the retriever-readerselector mechanism for Vietnamese open-domain texts, which outperformed two state-of-the-art question ...
arXiv:2204.07002v1
fatcat:oqrwofffpbd2fi5apwrc65gsde
Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answering
[article]
2021
arXiv
pre-print
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Open-domain Question Answering (OpenQA) is an important task in Natural Language Processing (NLP), which aims to answer a question in the form of natural language based on large-scale unstructured documents ...
Specifically, we begin with revisiting the origin and development of OpenQA systems. ...
In 2001, a QA system called MULDER [44] was designed to automatically answer open-domain factoid questions with a search engine (e.g., Google.com). ...
arXiv:2101.00774v3
fatcat:6evkg5cikjdp5fsi3ou3iqqkyq
Accelerating Real-Time Question Answering via Question Generation
[article]
2021
arXiv
pre-print
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answer without question encoding. ...
Although deep neural networks have achieved tremendous success for question answering (QA), they are still suffering from heavy computational and energy cost for real product deployment. ...
Related Work Open-Domain Question Answering Opendomain QA aims to answer any given factoid question without knowing the target domain. ...
arXiv:2009.05167v2
fatcat:sqy6s5f2jvbyfpltataeayoozm
Recent Trends in Deep Learning Based Open-Domain Textual Question Answering Systems
2020
IEEE Access
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INDEX TERMS Open-domain textual question answering, deep learning, machine reading comprehension, information retrieval. ...
Open-domain textual question answering (QA), which aims to answer questions from large data sources like Wikipedia or the web, has gained wide attention in recent years. ...
However, it is not beneficial in both efficiency and scalability since each passage needs to be encoded along with individual questions. ...
doi:10.1109/access.2020.2988903
fatcat:po4euxfronf3pob52qc2wcgrre
Differentiable Reasoning over a Virtual Knowledge Base
[article]
2020
arXiv
pre-print
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On HotpotQA, DrKIT leads to a 10% improvement over a BERT-based re-ranking approach to retrieving the relevant passages required to answer a question. ...
We consider the task of answering complex multi-hop questions using a corpus as a virtual knowledge base (KB). ...
End-to-end open-domain question answering with bertserini. arXiv preprint arXiv:1902.01718, 2019. Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. ...
arXiv:2002.10640v1
fatcat:2fcnpovwjjfdvfl36nvhoj3u54
Semantic Models for the First-stage Retrieval: A Comprehensive Review
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2103.04831v2 fatcat:7dminrg6cvefbcrggzf5dtfezaOther Versions
Therefore, it has been a long-term desire to build semantic models for the first-stage retrieval that can achieve high recall efficiently. ...
Moreover, we identify some open challenges and envision some future directions, with the hope of inspiring more researches on these important yet less investigated topics. ...
approaches for open-domain question answering. ...
arXiv:2103.04831v3
fatcat:6qa7hvc3jve3pcmo2mo4qsiefq
BioinQA: metadata-based multi-document QA system for addressing the issues in biomedical domain
2013
International Journal of Data Mining Modelling and Management
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While specialised information retrieval tools are not suitable for beginners, general purpose search engines are not intelligent enough to respond to domain specific questions. ...
The system constructs answers from multiple documents for complex comparison seeking questions. ...
They adapt an open domain QAS to answer genomic questions with emphasis on identifying term relations based on a linguistic-rich full-parser. ...
doi:10.1504/ijdmmm.2013.051921
fatcat:sm4dotonqrghrieptmzjo3ysme
Putting Question-Answering Systems into Practice
2019
ACM Transactions on Management Information Systems
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2018 pre-print arXiv:1804.07097v1 fatcat:5irmgszkqbabrcme2mku7zfqaqOther Versions
Conversely, question-answering systems change how humans interact with information systems: users can now ask specific questions and obtain a tailored answer - both conveniently in natural language. ...
approach for transfer learning in order to improve the performance of answer extraction. ...
More precisely, we draw upon a different dataset that Manuscript submitted to ACM contains general, open-domain question-answer pairs. ...
doi:10.1145/3309706
fatcat:blc5y2o36ze6zk3ezlt7o6ubaa
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