mlsanityData to 14 Oct 2026

RoleRAG: Enhancing LLM Role-Playing via Graph Guided Retrieval

arXiv 2505.18541 ↗First posted 24 May 2025cs.AIcited by 7

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Abstract (arXiv)

Large Language Models (LLMs) have shown promise in character imitation, enabling immersive and engaging conversations. However, they often generate content that is irrelevant or inconsistent with a character's background. We attribute these failures to: (1) the inability to accurately recall character-specific knowledge due to entity ambiguity, and (2) a lack of awareness of the character's cognitive boundaries. To address these issues, we propose RoleRAG, a retrieval-based framework that integrates efficient entity disambiguation for knowledge indexing with a boundary-aware retriever for extracting contextually appropriate information from a structured knowledge graph. Experiments on role-playing benchmarks show that RoleRAG's calibrated retrieval helps both general-purpose and role-specific LLMs better align with character knowledge and reduce hallucinated responses.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 18 of its 27 references that are in the map. First posted on arXiv 24 May 2025.

Builds on

18 of 27 references.

References · 18

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  3. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  4. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  5. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,195
  6. 2022Precise Zero-Shot Dense Retrieval without Relevance Labelscited by 517
  7. 2023LaMP: When Large Language Models Meet Personalizationcited by 437
  8. 2023Character-LLM: A Trainable Agent for Role-Playingcited by 339
  9. 2023ToolQA: A Dataset for LLM Question Answering with External Toolscited by 274
  10. 2023PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traitscited by 234
  11. 2024Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalizationcited by 208
  12. 2023InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviewscited by 179
6 more
  1. 2024CharacterEval: A Chinese Benchmark for Role-Playing Conversational Agent Evaluationcited by 143
  2. 2024Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignmentcited by 104
  3. 2024HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extractioncited by 93
  4. 2022Less is More: Learning to Refine Dialogue History for Personalized Dialogue Generationcited by 47
  5. 2024MMRole: A Comprehensive Framework for Developing and Evaluating Multimodal Role-Playing Agentscited by 21
  6. 2022Ontologically Faithful Generation of Non-Player Character Dialoguescited by 7

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 4.

7 papers.

  1. 2026Memory-Driven Role-Playing: Evaluation and Enhancement of Persona Knowledge Utilization in LLMscited by 5
  2. 2025Dynamic Context Adaptation for Consistent Role-Playing Agents with Retrieval-Augmented Generationscited by 4
  3. 2025When Retrieval Succeeds and Fails: Rethinking Retrieval-Augmented Generation for LLMscited by 1
  4. 2026From Facts to Insights: A Persona-Driven Dual Memory Framework and Dataset for Role-Playing Agentscited by 1
  5. 2025Living the Novel: A System for Generating Self-Training Timeline-Aware Conversational Agents from Novelscited by 0
  6. 2026Through the Lens of Character: Resolving Modality-Role Interference in Multimodal Role-Playing Agentcited by 0
  7. 2026BOOKMARKS: Efficient Active Storyline Memory for Role-playingcited by 0