Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Legal Search in Case Law and Statute Law   In this work we describe a method to identify document pairwise relevance in
the context of a typical legal document collection: limited resources, long
queries and long documents. We review the usage of generalized language models,
including supervised and unsupervised learning. We observe how our method,
while using text summaries, overperforms existing baselines based on full text,
and motivate potential improvement directions for future work.

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The categories of this paper are: cmp-lg
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The categories of this paper are: bayes-an
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The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
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The categories of this paper are: supr-con
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The categories of this paper are: q-fin
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The categories of this paper are: gr-qc
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The categories of this paper are: astro-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: atom-ph
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The categories of this paper are: solv-int
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The categories of this paper are: patt-sol
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The categories of this paper are: eess
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The categories of this paper are: nucl-ex
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The categories of this paper are: stat
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The categories of this paper are: hep-ex