Diverse, Controllable, and Keyphrase-Aware:A Corpus and Method for News Multi-Headline Generation
Table 3: News Article Retrieval Results
['Method', 'mAP@1 k=1', 'mAP@1 k=3', 'mAP@1 k=5', 'mAP@3 k=1', 'mAP@3 k=3', 'mAP@3 k=5', 'mAP@5 k=1', 'mAP@5 k=3', 'mAP@5 k=5', 'mAP@10 k=1', 'mAP@10 k=3', 'mAP@10 k=5']
Results. Similarly, our models perform much better than other keyphrase-agnostic baselines. BASE + Diverse outperforms BASE, but still performs worse than 7 keyphrase-aware generation models Generally, with the number of headline K increases, we can see that the performance of our keyphrase-aware generation models improves much higher than other baselines. We find that the mAP@10 of BASE + ParallelFuse (K=5) achieves 76.08, which is even better than HUMAN. These results demonstrate that our keyphrase-aware generation models can generate high-quality and diversity headlines.