| 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. |
| Outcome: | The proposed model improves on English and Chinese language benchmarks and shows that social orientation tags explain the outcomes of social interactions when used in neural models. |
Similar Papers
Social Influence Dialogue Systems: A Survey of Datasets and Models For Social Influence Tasks (2023.eacl-main)
Copied to clipboard
| Challenge: | Existing research focuses on task-oriented or open-domain dialogue systems with influence skills. |
| Approach: | They propose to define and introduce a category of social influence dialogue systems that influence users’ cognitive and emotional responses. |
| Outcome: | The proposed system is task-oriented or goal-oriented, but it is not open-domain. |
MuTual: A Dataset for Multi-Turn Dialogue Reasoning (2020.acl-main)
Copied to clipboard
| Challenge: | Existing non-task oriented dialogue systems can yield a relevant and fluent response, but sometimes make logical mistakes because of weak reasoning capabilities. |
| Approach: | They propose a dataset for multi-turn dialogue reasoning that uses annotated dialogues to train a machine to handle various reasoning problems. |
| Outcome: | Empirical results show that state-of-the-art methods only reach 71%, far behind human performance of 94%. |
Conversational Analysis of Daily Dialog Data using Polite Emotional Dialogue Acts (2022.lrec-1)
Copied to clipboard
| Challenge: | Literature suggests that analysis and use of social cues is beneficial for human-robot interaction. |
| Approach: | They propose to add linguistic politeness cues to conversational analysis and to find correlations between them. |
| Outcome: | The results confirm that utterances with Anger and Disgust are more likely to be polite than others. |
What Did You Refer to? Evaluating Co-References in Dialogue (2021.findings-acl)
Copied to clipboard
| Challenge: | Existing neural end-to-end dialogue models have limitations on exactly interpreting the linguistic structures in dialogue history context. |
| Approach: | They propose to directly measure the capability of neural end-to-end dialogue models on understanding the entity-oriented structures via question answering. |
| Outcome: | The proposed model can understand large-scale English and Chinese human human dialogues using a large-format dataset. |
Helpful or Hierarchical? Predicting the Communicative Strategies of Chat Participants, and their Impact on Success (2020.findings-emnlp)
Copied to clipboard
| 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. |
Sketching a Linguistically-Driven Reasoning Dialog Model for Social Talk (2022.acl-srw)
Copied to clipboard
| Challenge: | a new study shows that dialog systems that can hold social talk and make sense of conversational content are not efficient for context-sensitive natural language understanding and reasoning. |
| Approach: | They propose a linguistically-informed architecture to handle social talk in English . they propose linguistic models that fit the context-sensitive components into a Bayesian game-theoretic model . |
| Outcome: | The proposed architecture is based on corpus-based methods but does not track what is happening in a conversation. |
KTH Tangrams: A Dataset for Research on Alignment and Conceptual Pacts in Task-Oriented Dialogue (L18-1)
Copied to clipboard
| Challenge: | Existing studies on instructor-manipulator dialogue use disparate but similar datasets . a recent study examined the alignment of referring expressions (RL) in situated dialogue . |
| Approach: | They propose to use a corpus of referring expressions in a relatively free dialogue with physical features generated in simulated situations to study alignment in referring language. |
| Outcome: | The proposed datasets facilitate analysis of dialogic linguistic phenomena regarding alignment in the formation of referring expressions known as conceptual pacts. |
SalesBot: Transitioning from Chit-Chat to Task-Oriented Dialogues (2022.acl-long)
Copied to clipboard
| Challenge: | Until now, researchers have separated open-domain and task-oriented dialogues into two different types due to their different purposes. |
| Approach: | They propose a framework to automatically generate many dialogues without human involvement . the framework can be easily leveraged to generate unlimited dialogues in target scenarios . |
| Outcome: | The proposed framework can automatically generate many dialogues without human involvement . the human evaluation shows that the generated dialogues have a reasonable quality . |
SocialGaze: Improving the Integration of Human Social Norms in Large Language Models (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Increasingly, large language models (LLMs) are able to understand and rationalize socially acceptable behaviors, but they are often misaligned with human consensus. |
| Approach: | They propose a multi-step prompting framework that verbalizes a social situation from multiple perspectives before forming a judgment. |
| Outcome: | The proposed framework improves the alignment with human judgments by up to 11 F1 points with the GPT-3.5 model. |
Towards Identifying Social Bias in Dialog Systems: Framework, Dataset, and Benchmark (2022.findings-emnlp)
Copied to clipboard
Jingyan Zhou, Jiawen Deng, Fei Mi, Yitong Li, Yasheng Wang, Minlie Huang, Xin Jiang, Qun Liu, Helen Meng
| Challenge: | a number of safety concerns hinder the deployment of open-domain dialog systems, such as offensive languages and toxic behaviors, such social bias is difficult to detect. |
| Approach: | They propose a Dial-Bias Framework for analyzing social bias in conversations . they introduce a Chinese social bias dialog dataset and conduct in-depth ablation studies . |
| Outcome: | The proposed framework is the first annotated Chinese social bias dialog dataset . the proposed framework also provides a fine-grained dialog bias measurement benchmark . |