| Challenge: | Existing methods to characterize the association between two people do not account for nuances in the relationship between two individuals. |
| Approach: | They propose to use a set of dimensions to characterize the association between two people. |
| Outcome: | The proposed model can be automated using dialogue scripts from the TV show Friends. |
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Léa Deleris, Francesca Bonin, Elizabeth Daly, Stéphane Deparis, Yufang Hou, Charles Jochim, Yassine Lassoued, Killian Levacher
| Challenge: | Having an understanding of interpersonal relationships is helpful in many contexts. |
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VER: Unifying Verbalizing Entities and Relations (2023.findings-emnlp)
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| Challenge: | a new model for verbalizing entities and relations is proposed to help understand entities and relationships . a unified model for Verbalizing Entities and Relations is proposed . |
| Approach: | They propose a model that takes any entity or entity set as input and generates a sentence to represent entities and relations. |
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Interpersonal Relationship Labels for the CALLHOME Corpus (L18-1)
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| Challenge: | a lack of corpora makes exploration of this problem intractable, says nicolaus mills . mills: communication is one of the most invaluable tools humans have . |
| Approach: | a new study uses a corpus of interpersonal relationship labels to help identify relationships . a set of labels is available for download on the website of the cnn.org team . |
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From Text to Context: Contextualizing Language with Humans, Groups, and Communities for Socially Aware NLP (2024.naacl-tutorials)
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Adithya V Ganesan, Siddharth Mangalik, Vasudha Varadarajan, Nikita Soni, Swanie Juhng, João Sedoc, H. Andrew Schwartz, Salvatore Giorgi, Ryan L Boyd
| Challenge: | This tutorial will cover the latest techniques and libraries for doing so at each level of analysis. |
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Relational Summarization for Corpus Analysis (N18-1)
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| Challenge: | Existing methods for summarizing textual content are often ignored . relationshipal questions are ubiquitous and varied. |
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Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters (N19-1)
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| Challenge: | Existing literature analysis does not focus on roles of characters or on relationships between them. |
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How people talk about each other: Modeling Generalized Intergroup Bias and Emotion (2023.eacl-main)
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Venkata Subrahmanyan Govindarajan, Katherine Atwell, Barea Sinno, Malihe Alikhani, David I. Beaver, Junyi Jessy Li
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Your spouse needs professional help: Determining the Contextual Appropriateness of Messages through Modeling Social Relationships (2023.acl-long)
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| Challenge: | Existing methods for identifying offensive content in interpersonal communication are largely independent of context . prior work has shown the benefits of modeling context, such as demographics of annotators and readers, and the online community in which a message is said. |
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Automatically Inferring Gender Associations from Language (D19-1)
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| Challenge: | In this paper, we demonstrate that there are large-scale differences in the ways that people talk about women and men and that these differences vary across domains. |
| Approach: | They propose to integrate two datasets and a novel approach to automatically infer gender associations from language and find coherent word clusters and label clusters for the semantic concepts they represent. |
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Feature Interactions Reveal Linguistic Structure in Language Models (2023.findings-acl)
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| Challenge: | Existing features attribution methods for post-hoc interpretability ignore the existence of interactions between the effects of features on the prediction. |
| Approach: | They propose a grey box method to train models to perfection on a formal language classification task using PCFGs. |
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