Label Embedding Network: Learning Label Representation for Soft Training of Deep Networks
Table 3: Results of Label Embedding for the LCSTS text summarization task (W: Word model; C: Character model). The evaluation metric is ROUGE score (higher is better).
['[BOLD] LCSTS', 'ROUGE-1', 'ROUGE-2', 'ROUGE-L']
First, we show experimental results on the LCSTS text summarization task. The performance is measured by ROUGE-1, ROUGE-2, and ROUGE-L. As we can see, the proposed method performs much better compared to the baselines, with ROUGE-1 score of 31.7, ROUGE-2 score of 19.1, and ROUGE-L score of 29.1, improving by 1.6, 1.2, and 1.9, respectively. In fact, in terms of all of the three metrics, our implementation consistently beats the previous work, and the proposed method could further improve the results.