# One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles

arXiv: https://arxiv.org/abs/2108.09355 · HTML: https://mlsanity.com/paper/2108.09355/

## Key facts

- Cited by 39 papers in the map (data through 14 Oct 2026).
- Builds on 32 of its 50 references that are in the map.
- First posted on arXiv 20 Aug 2021.

## Builds on (most cited first, 30 of 32)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [A Diversity-Promoting Objective Function for Neural Conversation Models](https://mlsanity.com/paper/1510.03055/) (2015)
- [DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation](https://mlsanity.com/paper/1911.00536/) (2019)
- [Personalizing Dialogue Agents: I have a dog, do you have pets too?](https://mlsanity.com/paper/1801.07243/) (2018)
- [A Persona-Based Neural Conversation Model](https://mlsanity.com/paper/1603.06155/) (2016)
- [Key-Value Memory Networks for Directly Reading Documents](https://mlsanity.com/paper/1606.03126/) (2016)
- [Incorporating Copying Mechanism in Sequence-to-Sequence Learning](https://mlsanity.com/paper/1603.06393/) (2016)
- [Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models](https://mlsanity.com/paper/1507.04808/) (2015)
- [A Neural Conversational Model](https://mlsanity.com/paper/1506.05869/) (2015)
- [TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents](https://mlsanity.com/paper/1901.08149/) (2019)
- [A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues](https://mlsanity.com/paper/1605.06069/) (2016)
- [The Design and Implementation of XiaoIce, an Empathetic Social Chatbot](https://mlsanity.com/paper/1812.08989/) (2018)
- [Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory](https://mlsanity.com/paper/1704.01074/) (2017)
- [Dialogue Natural Language Inference](https://mlsanity.com/paper/1811.00671/) (2018)
- [Neural Responding Machine for Short-Text Conversation](https://mlsanity.com/paper/1503.02364/) (2015)
- [Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots](https://mlsanity.com/paper/1612.01627/) (2016)
- [A Neural Network Approach to Context-Sensitive Generation of Conversational Responses](https://mlsanity.com/paper/1506.06714/) (2015)
- [You Impress Me: Dialogue Generation via Mutual Persona Perception](https://mlsanity.com/paper/2004.05388/) (2020)
- [Learning to Select Knowledge for Response Generation in Dialog Systems](https://mlsanity.com/paper/1902.04911/) (2019)
- [Exploiting Persona Information for Diverse Generation of Conversational Responses](https://mlsanity.com/paper/1905.12188/) (2019)
- [Analogical Reasoning on Chinese Morphological and Semantic Relations](https://mlsanity.com/paper/1805.06504/) (2018)
- [Generate, Delete and Rewrite: A Three-Stage Framework for Improving Persona Consistency of Dialogue Generation](https://mlsanity.com/paper/2004.07672/) (2020)
- [Generating Persona Consistent Dialogues by Exploiting Natural Language Inference](https://mlsanity.com/paper/1911.05889/) (2019)
- [ReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation](https://mlsanity.com/paper/1907.05339/) (2019)
- [Pchatbot: A Large-Scale Dataset for Personalized Chatbot](https://mlsanity.com/paper/2009.13284/) (2020)
- [RTHN: A RNN-Transformer Hierarchical Network for Emotion Cause Extraction](https://mlsanity.com/paper/1906.01236/) (2019)
- [Conversational Contextual Cues: The Case of Personalization and History for Response Ranking](https://mlsanity.com/paper/1606.00372/) (2016)
- [Learning Personalized End-to-End Goal-Oriented Dialog](https://mlsanity.com/paper/1811.04604/) (2018)

## Built on by (most cited first, 30 of 39)

- [A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems](https://mlsanity.com/paper/2402.18013/) (2024)
- [From Matching to Generation: A Survey on Generative Information Retrieval](https://mlsanity.com/paper/2404.14851/) (2024)
- [Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts](https://mlsanity.com/paper/2406.10471/) (2024)
- [Keep Me Updated! Memory Management in Long-term Conversations](https://mlsanity.com/paper/2210.08750/) (2022)
- [Less is More: Learning to Refine Dialogue History for Personalized Dialogue Generation](https://mlsanity.com/paper/2204.08128/) (2022)
- [Memory Sandbox: Transparent and Interactive Memory Management for Conversational Agents](https://mlsanity.com/paper/2308.01542/) (2023)
- [Personalized LLM Response Generation with Parameterized Memory Injection](https://mlsanity.com/paper/2404.03565/) (2024)
- [A Survey of Personalization: From RAG to Agent](https://mlsanity.com/paper/2504.10147/) (2025)
- [RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generation](https://mlsanity.com/paper/2306.07206/) (2023)
- [Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona](https://mlsanity.com/paper/2305.11482/) (2023)
- [Target-aware Abstractive Related Work Generation with Contrastive Learning](https://mlsanity.com/paper/2205.13339/) (2022)
- [Personalized Text Generation with Fine-Grained Linguistic Control](https://mlsanity.com/paper/2402.04914/) (2024)
- [Recent Trends in Personalized Dialogue Generation: A Review of Datasets, Methodologies, and Evaluations](https://mlsanity.com/paper/2405.17974/) (2024)
- [Learning to Predict Persona Information forDialogue Personalization without Explicit Persona Description](https://mlsanity.com/paper/2111.15093/) (2021)
- [Preference-Conditioned Language-Guided Abstraction](https://mlsanity.com/paper/2402.03081/) (2024)
- [MPCODER: Multi-user Personalized Code Generator with Explicit and Implicit Style Representation Learning](https://mlsanity.com/paper/2406.17255/) (2024)
- [MIRACLE: Towards Personalized Dialogue Generation with Latent-Space Multiple Personal Attribute Control](https://mlsanity.com/paper/2310.18342/) (2023)
- [Mem-PAL: Towards Memory-based Personalized Dialogue Assistants for Long-term User-Agent Interaction](https://mlsanity.com/paper/2511.13410/) (2025)
- ["In Dialogues We Learn": Towards Personalized Dialogue Without Pre-defined Profiles through In-Dialogue Learning](https://mlsanity.com/paper/2403.03102/) (2024)
- [Unveiling Bias in Fairness Evaluations of Large Language Models: A Critical Literature Review of Music and Movie Recommendation Systems](https://mlsanity.com/paper/2401.04057/) (2024)
- [AutoPal: Autonomous Adaptation to Users for Personal AI Companionship](https://mlsanity.com/paper/2406.13960/) (2024)
- [A Survey of Personality, Persona, and Profile in Conversational Agents and Chatbots](https://mlsanity.com/paper/2401.00609/) (2023)
- [MORPHEUS: Modeling Role from Personalized Dialogue History by Exploring and Utilizing Latent Space](https://mlsanity.com/paper/2407.02345/) (2024)
- [MCP: Self-supervised Pre-training for Personalized Chatbots with Multi-level Contrastive Sampling](https://mlsanity.com/paper/2210.08753/) (2022)
- [Exploring the Design of Generative AI in Supporting Music-based Reminiscence for Older Adults](https://mlsanity.com/paper/2403.01413/) (2024)
- [Apollonion: Profile-centric Dialog Agent](https://mlsanity.com/paper/2404.08692/) (2024)
- [History of generative Artificial Intelligence (AI) chatbots: past, present, and future development](https://mlsanity.com/paper/2402.05122/) (2024)
- [Post Persona Alignment for Multi-Session Dialogue Generation](https://mlsanity.com/paper/2506.11857/) (2025)
- [ProfiLLM: An LLM-Based Framework for Implicit Profiling of Chatbot Users](https://mlsanity.com/paper/2506.13980/) (2025)
- [Learning from Streaming Data when Users Choose](https://mlsanity.com/paper/2406.01481/) (2024)

## Abstract (arXiv)

Personalized chatbots focus on endowing chatbots with a consistent personality to behave like real users, give more informative responses, and further act as personal assistants. Existing personalized approaches tried to incorporate several text descriptions as explicit user profiles. However, the acquisition of such explicit profiles is expensive and time-consuming, thus being impractical for large-scale real-world applications. Moreover, the restricted predefined profile neglects the language behavior of a real user and cannot be automatically updated together with the change of user interests. In this paper, we propose to learn implicit user profiles automatically from large-scale user dialogue history for building personalized chatbots. Specifically, leveraging the benefits of Transformer on language understanding, we train a personalized language model to construct a general user profile from the user's historical responses. To highlight the relevant historical responses to the input post, we further establish a key-value memory network of historical post-response pairs, and build a dynamic post-aware user profile. The dynamic profile mainly describes what and how the user has responded to similar posts in history. To explicitly utilize users' frequently used words, we design a personalized decoder to fuse two decoding strategies, including generating a word from the generic vocabulary and copying one word from the user's personalized vocabulary. Experiments on two real-world datasets show the significant improvement of our model compared with existing methods. Our code is available at https://github.com/zhengyima/DHAP