Papers by Carmen Banea
Building Location Embeddings from Physical Trajectories and Textual Representations (2020.aacl-main)
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| Challenge: | Using a dataset consisting of the location trajectories of 729 students over a seven month period, we investigate whether embeddings can represent aspects such as location presence or location functionality. |
| Approach: | They propose to use location embeddings to generate embeddables of sequences of locations a student has visited to identify surface properties captured in the representations. |
| Outcome: | The proposed models can be used to predict depression levels and area of study, and can be applied to complex tasks such as predicting area of studies and depression levels. |
Women’s Syntactic Resilience and Men’s Grammatical Luck: Gender-Bias in Part-of-Speech Tagging and Dependency Parsing (P19-1)
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| Challenge: | linguistic studies have shown the prevalence of various lexical and grammatical patterns in texts authored by a person of a particular gender, but models for part-of-speech tagging and dependency parsing have not adapted to account for these differences. |
| Approach: | They annotate the Wall Street Journal part of the Penn Treebank with the gender information of the articles’ authors and build taggers and parsers trained on this data. |
| Outcome: | The proposed model can account for gendered differences in syntactic tasks and highlight future venues for developing more accurate taggers and parsers. |
“Judge me by my size (noun), do you?” YodaLib: A Demographic-Aware Humor Generation Framework (2020.coling-main)
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| Challenge: | Humor is subjective and can be interpreted in different ways by different people. |
| Approach: | They propose an automatic method for filling the blanks in Mad Libs stories . they build upon the BERT platform to predict location-biased word fillings in incomplete sentences . |
| Outcome: | The proposed framework outperforms a semi-automated approach for filling the blanks in Mad Libs stories while accounting for the demographic backgrounds of the desired audience. |