Hello Again! LLM-powered Personalized Agent for Long-term Dialogue
On the map: LLM agents and tool use → Agent memory systems
Abstract (arXiv)
Open-domain dialogue systems have seen remarkable advancements with the development of large language models (LLMs). Nonetheless, most existing dialogue systems predominantly focus on brief single-session interactions, neglecting the real-world demands for long-term companionship and personalized interactions with chatbots. Crucial to addressing this real-world need are event summary and persona management, which enable reasoning for appropriate long-term dialogue responses. Recent progress in the human-like cognitive and reasoning capabilities of LLMs suggests that LLM-based agents could significantly enhance automated perception, decision-making, and problem-solving. In response to this potential, we introduce a model-agnostic framework, the Long-term Dialogue Agent (LD-Agent), which incorporates three independently tunable modules dedicated to event perception, persona extraction, and response generation. For the event memory module, long and short-term memory banks are employed to separately focus on historical and ongoing sessions, while a topic-based retrieval mechanism is introduced to enhance the accuracy of memory retrieval. Furthermore, the persona module conducts dynamic persona modeling for both users and agents. The integration of retrieved memories and extracted personas is subsequently fed into the generator to induce appropriate responses. The effectiveness, generality, and cross-domain capabilities of LD-Agent are empirically demonstrated across various illustrative benchmarks, models, and tasks. The code is released at https://github.com/leolee99/LD-Agent.
Key facts. Cited by 121 papers in the map (data through 7 Oct 2026). Placed in Agent memory systems, one of 16 directions in LLM agents and tool use. Builds on 48 of its 67 references that are in the map. First posted on arXiv 9 Jun 2024.
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- 2018Personalizing Dialogue Agents: I have a dog, do you have pets too?cited by 820
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- 2019GSN: A Graph-Structured Network for Multi-Party Dialoguescited by 26
- 2019Guiding Variational Response Generator to Exploit Personacited by 25
- 2022A Model-Agnostic Data Manipulation Method for Persona-based Dialogue Generationcited by 25
- 2019Dually Interactive Matching Network for Personalized Response Selection in Retrieval-Based Chatbotscited by 23
- 2019Getting To Know You: User Attribute Extraction from Dialoguescited by 19
- 2023Towards Robust Personalized Dialogue Generation via Order-Insensitive Representation Regularizationcited by 17
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- 2018Memory-augmented Dialogue Management for Task-oriented Dialogue Systemscited by 8
- 2021Detecting Speaker Personas from Conversational Textscited by 8
- 2023PK-ICR: Persona-Knowledge Interactive Context Retrieval for Grounded Dialoguecited by 6
- 2023UniMC: A Unified Framework for Long-Term Memory Conversation via Relevance Representation Learningcited by 6
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Citing papers per year: 2024: 10; 2025: 44; 2026: 67.
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- 2026Improving Multi-turn Dialogue Consistency with Self-Recall Thinking14 May 2026
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- 2026Hypotheses-Guided Self Distillation for Continual Personalization31 Aug 2026
- 2026FTA-Mem: Fact-Time-Affect Anchored Memory for Low-Density Long-Term Dialogue17 Aug 2026
- 2026Don't Scroll Back: Missing-Evidence Memory for Streaming Dialogue Summarization10 Aug 2026
- 2026Identifying Harm in Personalized, Generative AI Systems Requires User-Centered Auditing at the Interaction Level7 Aug 2026
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