mlsanityData to 7 Oct 2026

Neural Generation Meets Real People: Towards Emotionally Engaging Mixed-Initiative Conversations

arXiv 2008.12348 ↗First posted 27 Aug 2020cs.CL cs.AIcited by 24

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Abstract (arXiv)

We present Chirpy Cardinal, an open-domain dialogue agent, as a research platform for the 2019 Alexa Prize competition. Building an open-domain socialbot that talks to real people is challenging - such a system must meet multiple user expectations such as broad world knowledge, conversational style, and emotional connection. Our socialbot engages users on their terms - prioritizing their interests, feelings and autonomy. As a result, our socialbot provides a responsive, personalized user experience, capable of talking knowledgeably about a wide variety of topics, as well as chatting empathetically about ordinary life. Neural generation plays a key role in achieving these goals, providing the backbone for our conversational and emotional tone. At the end of the competition, Chirpy Cardinal progressed to the finals with an average rating of 3.6/5.0, a median conversation duration of 2 minutes 16 seconds, and a 90th percentile duration of over 12 minutes.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Aug 2020.

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Citing papers per year: 2021: 14; 2022: 7; 2023: 3.

24 papers.

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  1. 2022Evaluating Human-Language Model Interactioncited by 90
  2. 2021Anticipating Safety Issues in E2E Conversational AI: Framework and Toolingcited by 77
  3. 2021ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AIcited by 46
  4. 2021Hindsight: Posterior-guided training of retrievers for improved open-ended generationcited by 38
  5. 2021SaFeRDialogues: Taking Feedback Gracefully after Conversational Safety Failurescited by 37
  6. 2021The R-U-A-Robot Dataset: Helping Avoid Chatbot Deception by Detecting User Questions About Human or Non-Human Identitycited by 16
  7. 2022Multimodal Conversational AI: A Survey of Datasets and Approachescited by 16
  8. 2021Alquist 4.0: Towards Social Intelligence Using Generative Models and Dialogue Personalizationcited by 9
  9. 2022Robots-Dont-Cry: Understanding Falsely Anthropomorphic Utterances in Dialog Systemscited by 8
  10. 2021CASPR: A Commonsense Reasoning-based Conversational Socialbotcited by 6
  11. 2021Jurassic is (almost) All You Need: Few-Shot Meaning-to-Text Generation for Open-Domain Dialoguecited by 6
  12. 2021Proto: A Neural Cocktail for Generating Appealing Conversationscited by 5
12 more
  1. 2021Automatically Exposing Problems with Neural Dialog Modelscited by 5
  2. 2021Modeling Performance in Open-Domain Dialogue with PARADISEcited by 5
  3. 2021Athena 2.0: Contextualized Dialogue Management for an Alexa Prize SocialBotcited by 4
  4. 2022Improving Bot Response Contradiction Detection via Utterance Rewritingcited by 4
  5. 2022Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agentcited by 4
  6. 2022A Systematic Evaluation of Response Selection for Open Domain Dialoguecited by 4
  7. 2023A Transformer-based Response Evaluator for Open-Domain Spoken Conversationcited by 4
  8. 2021MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog Systemcited by 3
  9. 2023Safer Conversational AI as a Source of User Delightcited by 2
  10. 2021Medical Literature Mining and Retrieval in a Conversational Settingcited by 0
  11. 2022Miutsu: NTU's TaskBot for the Alexa Prizecited by 0
  12. 2023Athena 2.0: Discourse and User Modeling in Open Domain Dialoguecited by 0