mlsanityData to 7 Oct 2026

Retrieval-Free Knowledge-Grounded Dialogue Response Generation with Adapters

arXiv 2105.06232 ↗First posted 13 May 2021cs.CL cs.AIcited by 23

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Abstract (arXiv)

To diversify and enrich generated dialogue responses, knowledge-grounded dialogue has been investigated in recent years. The existing methods tackle the knowledge grounding challenge by retrieving the relevant sentences over a large corpus and augmenting the dialogues with explicit extra information. Despite their success, however, the existing works have drawbacks in inference efficiency. This paper proposes KnowExpert, a framework to bypass the explicit retrieval process and inject knowledge into the pre-trained language models with lightweight adapters and adapt to the knowledge-grounded dialogue task. To the best of our knowledge, this is the first attempt to tackle this challenge without retrieval in this task under an open-domain chit-chat scenario. The experimental results show that Knowexpert performs comparably with some retrieval-based baselines while being time-efficient in inference, demonstrating the effectiveness of our proposed method.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 37 of its 50 references that are in the map. First posted on arXiv 13 May 2021.

Builds on

37 of 50 references.

References · 37

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25 more
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Citing papers per year: 2021: 4; 2022: 6; 2023: 9; 2024: 2; 2025: 2.

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  1. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  2. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 888
  3. 2023Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigationcited by 123
  4. 2023Towards Mitigating Hallucination in Large Language Models via Self-Reflectioncited by 81
  5. 2022Contrastive Learning Reduces Hallucination in Conversationscited by 39
  6. 2021Think Before You Speak: Explicitly Generating Implicit Commonsense Knowledge for Response Generationcited by 26
  7. 2023Stabilized In-Context Learning with Pre-trained Language Models for Few Shot Dialogue State Trackingcited by 6
  8. 2023Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inferencecited by 6
  9. 2021CAiRE in DialDoc21: Data Augmentation for Information-Seeking Dialogue Systemcited by 5
  10. 2023KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue Generationcited by 5
  11. 2025Language Surgery in Multilingual Large Language Modelscited by 4
  12. 2022Inducer-tuning: Connecting Prefix-tuning and Adapter-tuningcited by 3
11 more
  1. 2023K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learningcited by 3
  2. 2024A Cause-Effect Look at Alleviating Hallucination of Knowledge-grounded Dialogue Generationcited by 3
  3. 2021Partner Personas Generation for Diverse Dialogue Generationcited by 1
  4. 2022Lexical Knowledge Internalization for Neural Dialog Generationcited by 1
  5. 2022Effective Transfer Learning for Low-Resource Natural Language Understandingcited by 1
  6. 2022Mind the Knowledge Gap: A Survey of Knowledge-enhanced Dialogue Systemscited by 1
  7. 2023Dialogue Agents 101: A Beginner's Guide to Critical Ingredients for Designing Effective Conversational Systemscited by 1
  8. 2023PICK: Polished & Informed Candidate Scoring for Knowledge-Grounded Dialogue Systemscited by 1
  9. 2025Efficient Tuning of Large Language Models for Knowledge-Grounded Dialogue Generationcited by 1
  10. 2021Taming the Beast: Learning to Control Neural Conversational Modelscited by 0
  11. 2024Adapter-based Approaches to Knowledge-enhanced Language Models -- A Surveycited by 0