Laura Burdick

Also published as: Laura Wendlandt


2019

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Identifying Visible Actions in Lifestyle Vlogs
Oana Ignat | Laura Burdick | Jia Deng | Rada Mihalcea
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

We consider the task of identifying human actions visible in online videos. We focus on the widely spread genre of lifestyle vlogs, which consist of videos of people performing actions while verbally describing them. Our goal is to identify if actions mentioned in the speech description of a video are visually present. We construct a dataset with crowdsourced manual annotations of visible actions, and introduce a multimodal algorithm that leverages information derived from visual and linguistic clues to automatically infer which actions are visible in a video.

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Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop
Sudipta Kar | Farah Nadeem | Laura Burdick | Greg Durrett | Na-Rae Han
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop

2018

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Factors Influencing the Surprising Instability of Word Embeddings
Laura Wendlandt | Jonathan K. Kummerfeld | Rada Mihalcea
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)

Despite the recent popularity of word embedding methods, there is only a small body of work exploring the limitations of these representations. In this paper, we consider one aspect of embedding spaces, namely their stability. We show that even relatively high frequency words (100-200 occurrences) are often unstable. We provide empirical evidence for how various factors contribute to the stability of word embeddings, and we analyze the effects of stability on downstream tasks.