Papers with joint-learning neural classification and generation schemes

1 papers
Metric-Type Identification for Multi-Level Header Numerical Tables in Scientific Papers (2021.eacl-main)

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Challenge: Numerical tables are used to present experimental results in scientific papers.
Approach: They propose a task to extract metric-types from multi-level header numerical tables . they propose two joint-learning neural classification and generation schemes .
Outcome: The proposed models handle in-header and out-of-headers metric-type identification problems.

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