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Pretrained Language Models for Dialogue Generation with Multiple Input Sources

arXiv 2010.07576 ↗First posted 15 Oct 2020cs.CLcited by 14

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Abstract (arXiv)

Large-scale pretrained language models have achieved outstanding performance on natural language understanding tasks. However, it is still under investigating how to apply them to dialogue generation tasks, especially those with responses conditioned on multiple sources. Previous work simply concatenates all input sources or averages information from different input sources. In this work, we study dialogue models with multiple input sources adapted from the pretrained language model GPT2. We explore various methods to fuse multiple separate attention information corresponding to different sources. Our experimental results show that proper fusion methods deliver higher relevance with dialogue history than simple fusion baselines.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Oct 2020.

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Citing papers per year: 2021: 3; 2022: 5; 2023: 3; 2024: 2; 2025: 1.

14 papers.

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  1. 2021ZeRO-Offload: Democratizing Billion-Scale Model Trainingcited by 339
  2. 2021DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarizationcited by 72
  3. 2022A Model-Agnostic Data Manipulation Method for Persona-based Dialogue Generationcited by 25
  4. 2021Focused Attention Improves Document-Grounded Generationcited by 24
  5. 2023SimOAP: Improve Coherence and Consistency in Persona-based Dialogue Generation via Over-sampling and Post-evaluationcited by 11
  6. 2022Commonsense and Named Entity Aware Knowledge Grounded Dialogue Generationcited by 8
  7. 2022Long-term Control for Dialogue Generation: Methods and Evaluationcited by 5
  8. 2023A Survey of Personality, Persona, and Profile in Conversational Agents and Chatbotscited by 5
  9. 2024LLMR: Knowledge Distillation with a Large Language Model-Induced Rewardcited by 3
  10. 2022Dynamically Retrieving Knowledge via Query Generation for Informative Dialogue Generationcited by 2
  11. 2023Multi-Step Dialogue Workflow Action Predictioncited by 2
  12. 2025Tgea: An error-annotated dataset and benchmark tasks for text generation from pretrained language modelscited by 1
2 more
  1. 2022MSDF: A General Open-Domain Multi-Skill Dialog Frameworkcited by 0
  2. 2024UniRQR: A Unified Model for Retrieval Decision, Query, and Response Generation in Internet-Based Knowledge Dialogue Systemscited by 0