Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dense Hierarchical Retrieval for Open-Domain Question Answering   Dense neural text retrieval has achieved promising results on open-domain
Question Answering (QA), where latent representations of questions and passages
are exploited for maximum inner product search in the retrieval process.
However, current dense retrievers require splitting documents into short
passages that usually contain local, partial, and sometimes biased context, and
highly depend on the splitting process. As a consequence, it may yield
inaccurate and misleading hidden representations, thus deteriorating the final
retrieval result. In this work, we propose Dense Hierarchical Retrieval (DHR),
a hierarchical framework that can generate accurate dense representations of
passages by utilizing both macroscopic semantics in the document and
microscopic semantics specific to each passage. Specifically, a document-level
retriever first identifies relevant documents, among which relevant passages
are then retrieved by a passage-level retriever. The ranking of the retrieved
passages will be further calibrated by examining the document-level relevance.
In addition, hierarchical title structure and two negative sampling strategies
(i.e., In-Doc and In-Sec negatives) are investigated. We apply DHR to
large-scale open-domain QA datasets. DHR significantly outperforms the original
dense passage retriever and helps an end-to-end QA system outperform the strong
baselines on multiple open-domain QA benchmarks.

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The categories of this paper are: ao-sci
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The categories of this paper are: alg-geom
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The categories of this paper are: q-alg
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The categories of this paper are: quant-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: supr-con
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The categories of this paper are: funct-an
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The categories of this paper are: dg-ga
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The categories of this paper are: chem-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: mtrl-th
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The categories of this paper are: bayes-an
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The categories of this paper are: math
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The categories of this paper are: math-ph
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The categories of this paper are: q-bio
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The categories of this paper are: physics