Views provided by UsageCounts
These are the trained BERT models for phrase alignment with the constrained tree edit distance algorithm, published at EMNLP2020. Yuki Arase and Jun'ichi Tsujii. 2020. Compositional Phrase Alignment and Beyond. in Proc. of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1611-1623. Source codes are available at GitHub When you use these models, please cite the following paper. @inproceedings{arase-tsujii-2020-compositional, title = "Compositional Phrase Alignment and Beyond", author = "Arase, Yuki and Tsujii, Jun{'}ichi", booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.emnlp-main.125", doi = "10.18653/v1/2020.emnlp-main.125", pages = "1611--1623" }
{"references": ["https://www.aclweb.org/anthology/2020.emnlp-main.125/"]}
Phrase alignment, BERT
Phrase alignment, BERT
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 12 |

Views provided by UsageCounts