Anna Rogers (Gladkova)

I am a post-doctoral associate in the Computer Science Department at Text Machine lab, University of Massachusetts (Lowell). I work on semantics and meaning representations, at the intersection of linguistics, natural language processing, and machine learning. I hold PhD from the Department of Language and Information Sciences at the University of Tokyo (Japan).

My current work focuses on interpretability of deep learning, evaluation of distributional meaning representations, and semantic compositionality. I also lead annotation projects for sentiment analysis and temporal reasoning.

Rogers, A., Drozd, A., & Li, B. (2017). The (Too Many) Problems of Analogical Reasoning with Word Vectors. In Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (* SEM 2017) (pp. 135–148).
Li, B., Liu, T., Zhao, Z., Tang, B., Drozd, A., Rogers, A., & Du, X. (2017). Investigating different syntactic context types and context representations for learning word embeddings. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (pp. 2411–2421).
Rogers, A. (2017). Multilingual computational lexicography: frame semantics meets distributional semantics (Ph.D. dissertation). University of Tokyo, Tokyo.

Gladkova, A., Drozd, A., & Matsuoka, S. (2016). Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn’t. In Proceedings of the NAACL-HLT SRW (pp. 47–54). San Diego, California, June 12-17, 2016: ACL.
Gladkova, A., & Drozd, A. (2016). Intrinsic evaluations of word embeddings: what can we do better? In Proceedings of The 1st Workshop on Evaluating Vector Space Representations for NLP (pp. 36–42). Berlin, Germany: ACL.
Drozd, A., Gladkova, A., & Matsuoka, S. (2016). Word embeddings, analogies, and machine learning: beyond king - man + woman = queen. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers (pp. 3519–3530). Osaka, Japan, December 11-17.
Santus, E., Gladkova, A., Evert, S., & Lenci, A. (2016). The CogALex-V shared task on the corpus-based identification of semantic relations. In Proceedings of the Workshop on Cognitive Aspects of the Lexicon (pp. 69–79). Osaka, Japan, December 11-17: ACL.

Drozd, A., Gladkova, A., & Matsuoka, S. (2015). Discovering aspectual classes of Russian verbs in untagged large corpora. In Proceedings of 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS) (pp. 61–68).
Drozd, A., Gladkova, A., & Matsuoka, S. (2015). Python, performance, and Natural Language Processing. In Proceedings of the 5th Workshop on Python for High-Performance and Scientific Computing (p. 1:1–1:10). New York, NY, USA: ACM.

English, French, Japanese, Ukrainian, Russian

Theoretical frameworks

Distributional semantics, frame semantics, cognitive linguistics, sociolinguistics

Programming & scripting

Python, R, Bash

Machine learning




7 May 2018: Distributional compositional semantics in the age of word embeddings. Tutorial T4 at LREC 2018, Miyazaki, Japan.
Tutorial website:

July 15 2016: Detecting linguistic relations with analogies: what works and what doesn't. Oral presentation at Google Tokyo seminar, Tokyo, Japan.