Papers with mutual understanding
Analysis of Sensation-transfer Dialogues in Motorsports (2024.lrec-main)
Copied to clipboard
| Challenge: | a recent study has examined the effects of subjective ideas on group performance in motorsports. |
| Approach: | They collected dialogues between drivers and engineers in motorsports to test this hypothesis . they defined "sensation" as a unique event unfolding in the mind of a speaker . |
| Outcome: | The results show that the more subjective information interlocutors exchange, the better the group performance in collaborative work. |
Chinese Whispers: A Multimodal Dataset for Embodied Language Grounding (2020.lrec-1)
Copied to clipboard
| Challenge: | In this paper, we introduce a multimodal dataset in which subjects are instructing each other how to assemble IKEA furniture. |
| Approach: | They propose a multimodal dataset in which subjects are instructing each other how to assemble IKEA furniture. |
| Outcome: | The proposed method avoids implicit experimenter biases by allowing subjects to instruct each other on the nature of the task: the process of the furniture assembly. |
How can NLP Help Revitalize Endangered Languages? A Case Study and Roadmap for the Cherokee Language (2022.acl-long)
Copied to clipboard
| Challenge: | There are an estimated 6000 to 7000 spoken languages in the world, and at least 43% of them are endangered. |
| Approach: | They propose three principles that may help NLP practitioners foster mutual understanding and collaboration with language communities and three ways in which NLP can potentially assist in language education. |
| Outcome: | The proposed methods can be used to enrich Cherokee language resources with machine-in-the-loop processing and to provide language education. |
Tailoring Vaccine Messaging with Common-Ground Opinions (2024.findings-naacl)
Copied to clipboard
Rickard Stureborg, Sanxing Chen, Roy Xie, Aayushi Patel, Christopher Li, Chloe Zhu, Tingnan Hu, Jun Yang, Bhuwan Dhingra
| Challenge: | Vaccine interventions aim to answer concerns expressed about vaccination. |
| Approach: | They propose a dataset to evaluate how well responses are tailored to a common-ground opinion . they find that GPT-4-Turbo performs significantly better than others . |
| Outcome: | The proposed dataset outperforms fine tuned LLMs on the task of tailoring vaccine responses to common-ground opinions. |
Mutual Gaze and Linguistic Repetition in a Multimodal Corpus (2022.lrec-1)
Copied to clipboard
| Challenge: | a study of linguistic repetitions and mutual understanding is conducted . we find no compelling correlation between mutual gaze and duration of the event . |
| Approach: | They investigate the correlation between mutual gaze and linguistic repetition, a form of alignment, which they take as evidence of mutual understanding. |
| Outcome: | The proposed method is based on the Multisimo corpus, a multimodal corpus which provides authentic task-based interactions among three participants. |
An Evaluation Framework for Multimodal Interaction (L18-1)
Copied to clipboard
| Challenge: | a framework for evaluating multimodal interactions is presented . it leverages the semantics of language and gesture to assess mutual understanding . consistent evaluation is required to test areas where the system needs improvement . |
| Approach: | They propose a framework for evaluating interactions between human and virtual agent . they use VoxML as a platform to model interactions using natural language and gesture . |
| Outcome: | The proposed framework assesses the level of mutual understanding and ease of communication between human and computer agents in a blocks world scenario. |
CommunityLM: Probing Partisan Worldviews from Language Models (2022.coling-1)
Copied to clipboard
| Challenge: | Political polarization is accelerating as political discourse diverges linguistically . et al. ( 2017) show that partisanship makes reliable predictions about an individual's word understanding . |
| Approach: | They propose a framework that probes community-specific responses to a survey using community language models CommunityLM. |
| Outcome: | The proposed framework can query the worldview of any group of people given a sufficiently large sample of their social media discussions or media diet. |
Can LLMs Ground when they (Don’t) Know: A Study on Direct and Loaded Political Questions (2025.acl-long)
Copied to clipboard
| Challenge: | Using large language models, interlocutors can reach mutual understanding even when they do not possess perfect knowledge. |
| Approach: | They examine whether loaded questions lead LLMs to engage in active grounding and correct false user beliefs in connection to their level of knowledge and their political bias. |
| Outcome: | The proposed model can answer direct knowledge questions and loaded questions that presuppose misinformation, while ignoring false user beliefs. |
Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey (2025.emnlp-main)
Copied to clipboard
Katerina Korre, Dimitris Tsirmpas, Nikos Gkoumas, Emma Cabalé, Danai Myrtzani, Theodoros Evgeniou, Ion Androutsopoulos, John Pavlopoulos
| Challenge: | Recent advances in LLMs enable artificial facilitation agents to not only moderate content, but also actively improve the quality of interactions. |
| Approach: | They propose a taxonomy on discussion quality evaluation and a new taxonomies for intervention and facilitation strategies. |
| Outcome: | The proposed methods synthesize ideas from Natural Language Processing (NLP) and Social Sciences to provide a taxonomy on discussion quality evaluation, and a roadmap of good practices and future research directions. |