Helpful or Hierarchical? Predicting the Communicative Strategies of Chat Participants, and their Impact on Success (2020.findings-emnlp)
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| Challenge: | a study of 5,500 chat interactions shows that successful communicators are successful in other domains. |
| Approach: | They annotate chat interactions with four dimensions of interaction styles to predict success . they find successful communicators are also successful in other domains . |
| Outcome: | The results show that successful communicators are successful in other domains. |
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| Challenge: | Using a model of the speaker's intentions, people can achieve pragmatic interpretations using a variety of reasoning abilities. |
| Approach: | They propose to model the interaction between speakers and listeners with different levels of pragmatic competence and to model their level of reasoning abilities. |
| Outcome: | The proposed model is based on a simulating language learning and conversing between speakers and listeners with different levels of reasoning abilities. |
Social Orientation: A New Feature for Dialogue Analysis (2024.lrec-main)
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| Challenge: | Existing studies on social orientations in dialogues show they improve performance in low-resource settings. |
| Approach: | They propose to use social orientation tags to model dialogue outcomes . they introduce a new set of dialogue utterances machine-labeled with social orientation tag. |
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Hierarchical Modeling for User Personality Prediction: The Role of Message-Level Attention (2020.acl-main)
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| Challenge: | Language processing is increasingly finding use as a supplement for questionnaires to assess psychological attributes of consenting individuals, but most approaches neglect to consider whether all documents of an individual are equally informative. |
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How did we get here? Summarizing conversation dynamics (2024.naacl-long)
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Yilun Hua, Nicholas Chernogor, Yuzhe Gu, Seoyeon Jeong, Miranda Luo, Cristian Danescu-Niculescu-Mizil
| Challenge: | Throughout a conversation, the way participants interact with each other is in constant flux. |
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Social Influence Dialogue Systems: A Survey of Datasets and Models For Social Influence Tasks (2023.eacl-main)
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| Challenge: | Existing research focuses on task-oriented or open-domain dialogue systems with influence skills. |
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| Outcome: | The proposed system is task-oriented or goal-oriented, but it is not open-domain. |
Conversation Model Fine-Tuning for Classifying Client Utterances in Counseling Dialogues (N19-1)
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| Challenge: | Recent surge of text-based online counseling applications enables us to collect and analyze interactions between counselors and clients. |
| Approach: | They develop a pre-trained conversation model that learns to classify client utterances into categories that help counselors in diagnosing client status and predicting counseling outcome. |
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Recipes for Building an Open-Domain Chatbot (2021.eacl-main)
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Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Eric Michael Smith, Y-Lan Boureau, Jason Weston
| Challenge: | Existing work shows that scaling models in the number of parameters and the size of the data they are trained on gives improved results, but other factors are important. |
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Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models (2024.findings-acl)
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| Challenge: | Effective interlocutors account for the uncertain goals, beliefs, and emotions of others. |
| Approach: | They propose to calibrate language models to better represent outcome uncertainty . they propose to use two methods to calibrated small open-source models . |
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Image-Chat: Engaging Grounded Conversations (2020.acl-main)
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| Challenge: | In order for machines to communicate with humans, they must understand the natural things that humans say about the world they live in and respond in kind. |
| Approach: | They propose to fuse a set of neural architectures using image and text representations to achieve this goal. |
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When does text prediction benefit from additional context? An exploration of contextual signals for chat and email messages (2021.naacl-industry)
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| Challenge: | Prior-message context provides the greatest lift in Teams (chat) scenario. |
| Approach: | They compare prior-message context with email and chat messages from Microsoft Teams and Outlook. |
| Outcome: | The proposed model outperforms existing models on two of the largest commercial communication platforms: Microsoft Teams and Outlook. |