Publications

My research career is just warming up. A few publications I have so far are curated by these services: Google Scholar, DBLP, and Semantic Scholar

    But here is a list:
  1. Thamme Gowda, Mozhdeh Gheini, and Jonathan May. Checks and strategies for enabling code-switched machine translation. arXiv preprint arXiv:2210.05096, 2022. [ Bibtex ]
  2. Tom Kocmi, Rachel Bawden, Ondrej Bojar, Anton Dvorkovich, Christian Federmann, Mark Fishel, Thamme Gowda, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Rebecca Knowles, Philipp Koehn, Christof Monz, Makoto Morishita, Masaaki Nagata, Toshiaki Nakazawa, Michal Novák, Martin Popel, Maja Popović, and Mariya Shmatova. Findings of the 2022 conference on machine translation (wmt22). In Proceedings of the Seventh Conference on Machine Translation, 1–45. Abu Dhabi, December 2022. Association for Computational Linguistics. URL: https://aclanthology.org/2022.wmt-1.1. [ Bibtex ]
  3. Thamme Gowda, Weiqiu You, Constantine Lignos, and Jonathan May. Macro-average: rare types are important too. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 1138–1157. Online, June 2021. Association for Computational Linguistics. URL: https://aclanthology.org/2021.naacl-main.90, doi:10.18653/v1/2021.naacl-main.90. [ Bibtex ]
  4. Thamme Gowda, Zhao Zhang, Chris Mattmann, and Jonathan May. Many-to-English machine translation tools, data, and pretrained models. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations, 306–316. Online, August 2021. Association for Computational Linguistics. URL: https://aclanthology.org/2021.acl-demo.37, doi:10.18653/v1/2021.acl-demo.37. [ Bibtex ]
  5. Thamme Gowda and Jonathan May. Finding the optimal vocabulary size for neural machine translation. In Findings of the Association for Computational Linguistics: EMNLP 2020, 3955–3964. Online, November 2020. Association for Computational Linguistics. URL: https://www.aclweb.org/anthology/2020.findings-emnlp.352, doi:10.18653/v1/2020.findings-emnlp.352. [ Bibtex ]
  6. Ninareh Mehrabi, Thamme Gowda, Fred Morstatter, Nanyun Peng, and Aram Galstyan. Man is to person as woman is to location: measuring gender bias in named entity recognition. In Proceedings of the 31st ACM Conference on Hypertext and Social Media, HT '20, 231–232. New York, NY, USA, 2020. Association for Computing Machinery. URL: https://doi.org/10.1145/3372923.3404804, doi:10.1145/3372923.3404804. [ Bibtex ]
  7. Elizabeth Boschee, Joel Barry, Jayadev Billa, Marjorie Freedman, Thamme Gowda, Constantine Lignos, Chester Palen-Michel, Michael Pust, Banriskhem Kayang Khonglah, Srikanth Madikeri, Jonathan May, and Scott Miller. SARAL: a low-resource cross-lingual domain-focused information retrieval system for effective rapid document triage. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 19–24. Florence, Italy, July 2019. Association for Computational Linguistics. URL: https://www.aclweb.org/anthology/P19-3004, doi:10.18653/v1/P19-3004. [ Bibtex ]
  8. Xiaoman Pan, Thamme Gowda, Heng Ji, Jonathan May, and Scott Miller. Cross-lingual joint entity and word embedding to improve entity linking and parallel sentence mining. In Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019), 56–66. Hong Kong, China, November 2019. Association for Computational Linguistics. URL: https://www.aclweb.org/anthology/D19-6107, doi:10.18653/v1/D19-6107. [ Bibtex ]
  9. Kyle Hundman, Thamme Gowda, Mayank Kejriwal, and Benedikt Boecking. Always lurking: understanding and mitigating bias in online human trafficking detection. In Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, AIES '18, 137–143. New York, NY, USA, 2018. Association for Computing Machinery. URL: https://doi.org/10.1145/3278721.3278782, doi:10.1145/3278721.3278782. [ Bibtex ]
  10. Kiri Wagstaff, Raymond Francis, Thamme Gowda, You Lu, Ellen Riloff, Karanjeet Singh, and Nina Lanza. Mars target encyclopedia: rock and soil composition extracted from the literature. Proceedings of the AAAI Conference on Artificial Intelligence, Apr. 2018. URL: https://ojs.aaai.org/index.php/AAAI/article/view/11412. [ Bibtex ]
  11. Kiri Wagstaff, You Lu, Alice Stanboli, Kevin Grimes, Thamme Gowda, and Jordan Padams. Deep mars: cnn classification of mars imagery for the pds imaging atlas. Proceedings of the AAAI Conference on Artificial Intelligence, Apr. 2018. URL: https://ojs.aaai.org/index.php/AAAI/article/view/11404. [ Bibtex ]
  12. Thamme Gowda, Kyle Hundman, and Chris A. Mattmann. An approach for automatic and large scale image forensics. In Proceedings of the 2nd International Workshop on Multimedia Forensics and Security, MFSec '17, 16–20. New York, NY, USA, 2017. Association for Computing Machinery. URL: https://doi.org/10.1145/3078897.3080536, doi:10.1145/3078897.3080536. [ Bibtex ]
  13. Thamme Gowda and Chris A. Mattmann. Clustering web pages based on structure and style similarity (application paper). In 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI), volume, 175–180. 2016. doi:10.1109/IRI.2016.30. [ Bibtex ]