mlsanityData to 7 Oct 2026

CAiRE in DialDoc21: Data Augmentation for Information-Seeking Dialogue System

arXiv 2106.03530 ↗First posted 7 Jun 2021cs.CL cs.AIcited by 5

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Abstract (arXiv)

Information-seeking dialogue systems, including knowledge identification and response generation, aim to respond to users with fluent, coherent, and informative responses based on users' needs, which. To tackle this challenge, we utilize data augmentation methods and several training techniques with the pre-trained language models to learn a general pattern of the task and thus achieve promising performance. In DialDoc21 competition, our system achieved 74.95 F1 score and 60.74 Exact Match score in subtask 1, and 37.72 SacreBLEU score in subtask 2. Empirical analysis is provided to explain the effectiveness of our approaches.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 21 of its 24 references that are in the map. First posted on arXiv 7 Jun 2021.

Builds on

21 of 24 references.

References · 21

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  10. 2020Sequential Latent Knowledge Selection for Knowledge-Grounded Dialoguecited by 82
  11. 2019Learning to Select Knowledge for Response Generation in Dialog Systemscited by 80
  12. 2020MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Modelscited by 74
9 more
  1. 2020DoQA -- Accessing Domain-Specific FAQs via Conversational QAcited by 42
  2. 2020XPersona: Evaluating Multilingual Personalized Chatbotcited by 36
  3. 2020Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systemscited by 35
  4. 2020Plug-and-Play Conversational Modelscited by 30
  5. 2021Retrieval-Free Knowledge-Grounded Dialogue Response Generation with Adapterscited by 23
  6. 2019Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variablescited by 21
  7. 2019Technical report on Conversational Question Answeringcited by 18
  8. 2021ERICA: An Empathetic Android Companion for Covid-19 Quarantinecited by 8
  9. 2021Nora: The Well-Being Coachcited by 4

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Cited by year

Citing papers per year: 2022: 3; 2023: 1; 2024: 0; 2025: 1.

5 papers.

  1. 2022Can Question Rewriting Help Conversational Question Answering?cited by 8
  2. 2022UniGDD: A Unified Generative Framework for Goal-Oriented Document-Grounded Dialoguecited by 8
  3. 2023Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inferencecited by 6
  4. 2022Topic-Aware Response Generation in Task-Oriented Dialogue with Unstructured Knowledge Accesscited by 3
  5. 2025MonoTODia: Translating Monologue Requests to Task-Oriented Dialoguescited by 0