paper-with-me

홈 › Papers

Grounding Conversations with Improvised Dialogues

2020-04-20 · ACL 2020 6 · Hyundong Cho, Jonathan May

Effective dialogue involves grounding, the process of establishing mutual knowledge that is essential for communication between people. Modern dialogue systems are not explicitly trained to build common ground, and therefore overlook this important aspect of communication. Improvisational theater (improv) intrinsically contains a high proportion of dialogue focused on building common ground, and makes use of the yes-and principle, a strong grounding speech act, to establish coherence and an actionable objective reality. We collect a corpus of more than 26,000 yes-and turns, transcribing them from improv dialogues and extracting them from larger, but more sparsely populated movie script dialogue corpora, via a bootstrapped classifier. We fine-tune chit-chat dialogue systems with our corpus to encourage more grounded, relevant conversation and confirm these findings with human evaluations.

📄 PDF Abstract BibTeX arXiv:2004.09544

Code (1)

wise-east/spolin 공식 구현 pytorch

Similar Papers 제목 키워드 기반

Evaluating Very Long-Term Conversational Memory of LLM Agents

2024-02-27 · Adyasha Maharana, Dong-Ho Lee, Sergey Tulyakov, Mohit Bansal 외

Existing works on long-term open-domain dialogues focus on evaluating model responses within contexts spanning no more than five chat sessions. Despite advancements in long-context large language models (LLMs) and retrie…

AvgDialogue GenerationMulti-modal Dialogue GenerationQuestion Answering+2

Bridging Information Gaps in Dialogues With Grounded Exchanges Using Knowledge Graphs

2024-08-02 · Phillip Schneider, Nektarios Machner, Kristiina Jokinen, Florian Matthes

Knowledge models are fundamental to dialogue systems for enabling conversational interactions, which require handling domain-specific knowledge. Ensuring effective communication in information-providing conversations ent…

In-Context LearningKnowledge Graphs

A Linguistic Comparison between Human and ChatGPT-Generated Conversations

2024-01-29 · Morgan Sandler, Hyesun Choung, Arun Ross, Prabu David

This study explores linguistic differences between human and LLM-generated dialogues, using 19.5K dialogues generated by ChatGPT-3.5 as a companion to the EmpathicDialogues dataset. The research employs Linguistic Inquir…

Language ModelingLanguage ModellingMisinformation

BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets

2022-10-23 · Minju Kim, Chaehyeong Kim, Yongho Song, Seung-won Hwang 외

To build open-domain chatbots that are able to use diverse communicative skills, we propose a novel framework BotsTalk, where multiple agents grounded to the specific target skills participate in a conversation to automa…

Acted vs. Improvised: Domain Adaptation for Elicitation Approaches in Audio-Visual Emotion Recognition

2021-04-05 · Haoqi Li, Yelin Kim, Cheng-Hao Kuo, Shrikanth Narayanan

Key challenges in developing generalized automatic emotion recognition systems include scarcity of labeled data and lack of gold-standard references. Even for the cues that are labeled as the same emotion category, the v…

Domain AdaptationEmotion RecognitionTransfer Learning