Aligning Sentences in a Paragraph-Paraphrased Corpus with New Embedding-based Similarity Measures
Aleksandra Smolka Smolka, Hsin-Min Wang, Jason S. Chang, Keh-Yih Su
- Anthology ID:
- 2022.ijclclp-2.1
- Volume:
- International Journal of Computational Linguistics & Chinese Language Processing, Volume 27, Number 2, December 2022
- Month:
- December
- Year:
- 2022
- Address:
- Taipei, Taiwan
- Editors:
- Berlin Chen, Hung-Yu Kao
- Venue:
- IJCLCLP
- SIG:
- Publisher:
- Association for Computational Linguistics and Chinese Language Processing
- Note:
- Pages:
- Language:
- URL:
- https://aclanthology.org/2022.ijclclp-2.1
- DOI:
- Cite (ACL):
- Aleksandra Smolka Smolka, Hsin-Min Wang, Jason S. Chang, and Keh-Yih Su. 2022. Aligning Sentences in a Paragraph-Paraphrased Corpus with New Embedding-based Similarity Measures. In International Journal of Computational Linguistics & Chinese Language Processing, Volume 27, Number 2, December 2022, Taipei, Taiwan. Association for Computational Linguistics and Chinese Language Processing.
- Cite (Informal):
- Aligning Sentences in a Paragraph-Paraphrased Corpus with New Embedding-based Similarity Measures (Smolka et al., IJCLCLP 2022)
- PDF:
- https://preview.aclanthology.org/retraction/2022.ijclclp-2.1.pdf