bookmarks (hide)35
- Control text generation for language models like GPT2. We use PPLM, an approach that combines a language model with attribute models to control the style.
publications (hide)110
- (2019)cite arxiv:1908.10084Comment: Published at EMNLP 2019.
- MIT press, (2009)
- Proceedings of MT summit IX, page 63--70. (2003)
- Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization, page 65--72. (2005)
- Text summarization branches out, page 74--81. (2004)
- (2021)cite arxiv:2101.00774Comment: 20 pages.
- (2020)cite arxiv:2004.07159Comment: Accepted at EMNLP 2020.
- Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, page 1--9. (2020)
- arXiv preprint arXiv:1902.01718, (2019)
- arXiv preprint arXiv:1704.00051, (2017)
- Trec, 99, page 77--82. (1999)
- Natural Language Engineering, 9 (3): 231 (2003)
- Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval, page 973--976. (2013)
- Synthesis Lectures on Human Language Technologies, 7 (2): 1--178 (2014)
- Neural computation, 9 (8): 1735--1780 (1997)
- Advances in neural information processing systems, page 5998--6008. (2017)
- arXiv preprint arXiv:1705.02364, (2017)
- Twenty-Fourth International Joint Conference on Artificial Intelligence, (2015)
- (2016)cite arxiv:1607.04606Comment: Accepted to TACL. The two first authors contributed equally.
- Advances in neural information processing systems, (2016)
