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Learning Fine-grained Fact-Article Correspondence in Legal Cases
[article]
2021
arXiv
pre-print
Automatically recommending relevant law articles to a given legal case has attracted much attention as it can greatly release human labor from searching over the large database of laws. However, current researches only support coarse-grained recommendation where all relevant articles are predicted as a whole without explaining which specific fact each article is relevant with. Since one case can be formed of many supporting facts, traversing over them to verify the correctness of recommendation
arXiv:2104.10726v3
fatcat:o2ht6u6bifezffvy6nbkxyctrm