Gunrock: A Social Bot for Complex and Engaging Long Conversations
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Abstract (arXiv)
Gunrock is the winner of the 2018 Amazon Alexa Prize, as evaluated by coherence and engagement from both real users and Amazon-selected expert conversationalists. We focus on understanding complex sentences and having in-depth conversations in open domains. In this paper, we introduce some innovative system designs and related validation analysis. Overall, we found that users produce longer sentences to Gunrock, which are directly related to users' engagement (e.g., ratings, number of turns). Additionally, users' backstory queries about Gunrock are positively correlated to user satisfaction. Finally, we found dialog flows that interleave facts and personal opinions and stories lead to better user satisfaction.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Oct 2019.
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Citing papers per year: 2021: 4; 2022: 5; 2023: 1; 2024: 3; 2025: 1.
14 papers.
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- 2021ESPnet-SLU: Advancing Spoken Language Understanding through ESPnetcited by 53
- 2022Neural Approaches to Conversational Information Retrievalcited by 41
- 2021Few-shot Intent Classification and Slot Filling with Retrieved Examplescited by 35
- 2022A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understandingcited by 18
- 2022Token-level Sequence Labeling for Spoken Language Understanding using Compositional End-to-End Modelscited by 10
- 2024On the Evaluation of Speech Foundation Models for Spoken Language Understandingcited by 9
- 2022Two-Pass Low Latency End-to-End Spoken Language Understandingcited by 8
- 2021Automatically Exposing Problems with Neural Dialog Modelscited by 5
- 2022Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agentcited by 4
- 2024Apollonion: Profile-centric Dialog Agentcited by 4
- 2021Low-Resource Adaptation of Open-Domain Generative Chatbotscited by 2
- 2023Integrating Pretrained ASR and LM to Perform Sequence Generation for Spoken Language Understandingcited by 2
- 2025Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments26 Jun 2025
- 2024Policy-driven Knowledge Selection and Response Generation for Document-grounded Dialogue21 Oct 2024
- 2024On the Evaluation of Speech Foundation Models for Spoken Language Understanding14 Jun 2024
- 2024Apollonion: Profile-centric Dialog Agent10 Apr 2024
- 2023Integrating Pretrained ASR and LM to Perform Sequence Generation for Spoken Language Understanding20 Jul 2023
- 2022A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding10 Nov 2022
- 2022Token-level Sequence Labeling for Spoken Language Understanding using Compositional End-to-End Models27 Oct 2022
- 2022Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent25 Jul 2022
- 2022Two-Pass Low Latency End-to-End Spoken Language Understanding14 Jul 2022
- 2022Neural Approaches to Conversational Information Retrieval13 Jan 2022
- 2021ESPnet-SLU: Advancing Spoken Language Understanding through ESPnet29 Nov 2021
- 2021Automatically Exposing Problems with Neural Dialog Models14 Sep 2021
2 more
- 2024Apollonion: Profile-centric Dialog Agentcited by 4
- 2024Apollonion: Profile-centric Dialog Agent10 Apr 2024
- 2021ESPnet-SLU: Advancing Spoken Language Understanding through ESPnetcited by 53
- 2022Neural Approaches to Conversational Information Retrievalcited by 41
- 2021Few-shot Intent Classification and Slot Filling with Retrieved Examplescited by 35
- 2022A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understandingcited by 18
- 2022Token-level Sequence Labeling for Spoken Language Understanding using Compositional End-to-End Modelscited by 10
- 2024On the Evaluation of Speech Foundation Models for Spoken Language Understandingcited by 9
- 2022Two-Pass Low Latency End-to-End Spoken Language Understandingcited by 8
- 2021Automatically Exposing Problems with Neural Dialog Modelscited by 5
- 2022Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agentcited by 4
- 2021Low-Resource Adaptation of Open-Domain Generative Chatbotscited by 2
- 2023Integrating Pretrained ASR and LM to Perform Sequence Generation for Spoken Language Understandingcited by 2
- 2024Policy-driven Knowledge Selection and Response Generation for Document-grounded Dialoguecited by 0
- 2024Policy-driven Knowledge Selection and Response Generation for Document-grounded Dialogue21 Oct 2024
- 2024On the Evaluation of Speech Foundation Models for Spoken Language Understanding14 Jun 2024
- 2023Integrating Pretrained ASR and LM to Perform Sequence Generation for Spoken Language Understanding20 Jul 2023
- 2022A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding10 Nov 2022
- 2022Token-level Sequence Labeling for Spoken Language Understanding using Compositional End-to-End Models27 Oct 2022
- 2022Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent25 Jul 2022
- 2022Two-Pass Low Latency End-to-End Spoken Language Understanding14 Jul 2022
- 2022Neural Approaches to Conversational Information Retrieval13 Jan 2022
- 2021ESPnet-SLU: Advancing Spoken Language Understanding through ESPnet29 Nov 2021
- 2021Automatically Exposing Problems with Neural Dialog Models14 Sep 2021
- 2021Low-Resource Adaptation of Open-Domain Generative Chatbots13 Aug 2021
- 2021Few-shot Intent Classification and Slot Filling with Retrieved Examples12 Apr 2021