# Generate, Delete and Rewrite: A Three-Stage Framework for Improving Persona Consistency of Dialogue Generation

arXiv: https://arxiv.org/abs/2004.07672 · HTML: https://mlsanity.com/paper/2004.07672/

## Key facts

- Cited by 41 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Apr 2020.

## Built on by (most cited first, 30 of 41)

- [A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems](https://mlsanity.com/paper/2402.18013/) (2024)
- [Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey](https://mlsanity.com/paper/2105.04387/) (2021)
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- [BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data](https://mlsanity.com/paper/2106.06169/) (2021)
- [PLACES: Prompting Language Models for Social Conversation Synthesis](https://mlsanity.com/paper/2302.03269/) (2023)
- [CharacterChat: Learning towards Conversational AI with Personalized Social Support](https://mlsanity.com/paper/2308.10278/) (2023)
- [The Oscars of AI Theater: A Survey on Role-Playing with Language Models](https://mlsanity.com/paper/2407.11484/) (2024)
- [Harnessing the Power of Large Language Models for Empathetic Response Generation: Empirical Investigations and Improvements](https://mlsanity.com/paper/2310.05140/) (2023)
- [One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles](https://mlsanity.com/paper/2108.09355/) (2021)
- [Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods](https://mlsanity.com/paper/2203.05227/) (2022)
- [A Model-Agnostic Data Manipulation Method for Persona-based Dialogue Generation](https://mlsanity.com/paper/2204.09867/) (2022)
- [COSPLAY: Concept Set Guided Personalized Dialogue Generation Across Both Party Personas](https://mlsanity.com/paper/2205.00872/) (2022)
- [Thinking Clearly, Talking Fast: Concept-Guided Non-Autoregressive Generation for Open-Domain Dialogue Systems](https://mlsanity.com/paper/2109.04084/) (2021)
- [Towards Robust Personalized Dialogue Generation via Order-Insensitive Representation Regularization](https://mlsanity.com/paper/2305.12782/) (2023)
- [Towards Personalized Answer Generation in E-Commerce via Multi-Perspective Preference Modeling](https://mlsanity.com/paper/2112.13556/) (2021)
- [Leveraging Large Language Models for Automated Dialogue Analysis](https://mlsanity.com/paper/2309.06490/) (2023)
- [Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning](https://mlsanity.com/paper/2310.10735/) (2023)
- [Learning Implicit User Profiles for Personalized Retrieval-Based Chatbot](https://mlsanity.com/paper/2108.07935/) (2021)
- [Learning to Predict Persona Information forDialogue Personalization without Explicit Persona Description](https://mlsanity.com/paper/2111.15093/) (2021)
- [SimOAP: Improve Coherence and Consistency in Persona-based Dialogue Generation via Over-sampling and Post-evaluation](https://mlsanity.com/paper/2305.11130/) (2023)
- [Transferable Persona-Grounded Dialogues via Grounded Minimal Edits](https://mlsanity.com/paper/2109.07713/) (2021)
- [Sketch and Customize: A Counterfactual Story Generator](https://mlsanity.com/paper/2104.00929/) (2021)
- [Don't Forget Your ABC's: Evaluating the State-of-the-Art in Chat-Oriented Dialogue Systems](https://mlsanity.com/paper/2212.09180/) (2022)
- [A Cooperative Memory Network for Personalized Task-oriented Dialogue Systems with Incomplete User Profiles](https://mlsanity.com/paper/2102.08322/) (2021)
- [When Memory Updates but Behavior Does Not: Repairing Implicit Stale Dependencies in Personalized Agent Responses](https://mlsanity.com/paper/2608.01619/) (2026)
- [Towards Standard Criteria for human evaluation of Chatbots: A Survey](https://mlsanity.com/paper/2105.11197/) (2021)
- [Context-dependent Instruction Tuning for Dialogue Response Generation](https://mlsanity.com/paper/2311.07006/) (2023)
- [Controllable Contextualized Image Captioning: Directing the Visual Narrative through User-Defined Highlights](https://mlsanity.com/paper/2407.11449/) (2024)
- [Post Persona Alignment for Multi-Session Dialogue Generation](https://mlsanity.com/paper/2506.11857/) (2025)
- [Stylistic Retrieval-based Dialogue System with Unparallel Training Data](https://mlsanity.com/paper/2109.05477/) (2021)

## Abstract (arXiv)

Maintaining a consistent personality in conversations is quite natural for human beings, but is still a non-trivial task for machines. The persona-based dialogue generation task is thus introduced to tackle the personality-inconsistent problem by incorporating explicit persona text into dialogue generation models. Despite the success of existing persona-based models on generating human-like responses, their one-stage decoding framework can hardly avoid the generation of inconsistent persona words. In this work, we introduce a three-stage framework that employs a generate-delete-rewrite mechanism to delete inconsistent words from a generated response prototype and further rewrite it to a personality-consistent one. We carry out evaluations by both human and automatic metrics. Experiments on the Persona-Chat dataset show that our approach achieves good performance.