 The correspondent merging results is learned by the attention maps in attention mechanism. With the proposed method, we can recognize the structure of tables well, even for complex tables. SEM can achieve an average F-Measure of 96.9%DIFDELCMD < \\%%% %DIF < on the SciTSR dataset which outperforms other methods by a large margin.
<coherence>  The correspondent merging results is learned by the attention maps in attention mechanism. With the proposed method, we can recognize the structure of tables well, even for complex tables. SEM can achieve an average F-Measure of 96.9%DIFDELCMD < \\%%% %DIF < on the SciTSR dataset which outperforms other methods by a large margin.
 The correspondent merging results is learned %DIFDELCMD < \\%%% %DIF < on the SciTSR dataset which outperforms other methods by a large margin.