# Neeko: Leveraging Dynamic LoRA for Efficient Multi-Character Role-Playing Agent

arXiv: https://arxiv.org/abs/2402.13717 · HTML: https://mlsanity.com/paper/2402.13717/

## Key facts

- Cited by 52 papers in the map (data through 14 Oct 2026).
- Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use.
- Builds on 17 of its 32 references that are in the map.
- First posted on arXiv 21 Feb 2024.

## Placed in

- LLM agents and tool use / [Social simulation and multi-agent debate](https://mlsanity.com/agents/social-simulation-and-multi-agent-debate/)

## Builds on (most cited first, 17 of 17)

- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [Transformer Feed-Forward Layers Are Key-Value Memories](https://mlsanity.com/paper/2012.14913/) (2020)
- [Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning](https://mlsanity.com/paper/2012.13255/) (2020)
- [LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition](https://mlsanity.com/paper/2307.13269/) (2023)
- [Character-LLM: A Trainable Agent for Role-Playing](https://mlsanity.com/paper/2310.10158/) (2023)
- [Learning Factored Representations in a Deep Mixture of Experts](https://mlsanity.com/paper/1312.4314/) (2013)
- [DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation](https://mlsanity.com/paper/2210.07558/) (2022)
- [CharacterEval: A Chinese Benchmark for Role-Playing Conversational Agent Evaluation](https://mlsanity.com/paper/2401.01275/) (2024)
- [When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications](https://mlsanity.com/paper/2310.18339/) (2023)
- [MELO: Enhancing Model Editing with Neuron-Indexed Dynamic LoRA](https://mlsanity.com/paper/2312.11795/) (2023)
- [Lifelong Language Pretraining with Distribution-Specialized Experts](https://mlsanity.com/paper/2305.12281/) (2023)
- [AdaNet: Adaptive Structural Learning of Artificial Neural Networks](https://mlsanity.com/paper/1607.01097/) (2016)
- [Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterances](https://mlsanity.com/paper/2204.10825/) (2022)
- [Assessing Knowledge Editing in Language Models via Relation Perspective](https://mlsanity.com/paper/2311.09053/) (2023)
- [Unsupervised Enrichment of Persona-grounded Dialog with Background Stories](https://mlsanity.com/paper/2106.08364/) (2021)
- [Telling Stories through Multi-User Dialogue by Modeling Character Relations](https://mlsanity.com/paper/2105.15054/) (2021)

## Built on by (most cited first, 30 of 52)

- [From Persona to Personalization: A Survey on Role-Playing Language Agents](https://mlsanity.com/paper/2404.18231/) (2024)
- [PersonaGym: Evaluating Persona Agents and LLMs](https://mlsanity.com/paper/2407.18416/) (2024)
- [From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents](https://mlsanity.com/paper/2412.03563/) (2024)
- [A Survey on LLM-based Multi-Agent System: Recent Advances and New Frontiers in Application](https://mlsanity.com/paper/2412.17481/) (2024)
- [The Oscars of AI Theater: A Survey on Role-Playing with Language Models](https://mlsanity.com/paper/2407.11484/) (2024)
- [Personality Alignment of Large Language Models](https://mlsanity.com/paper/2408.11779/) (2024)
- [A Survey of Personalization: From RAG to Agent](https://mlsanity.com/paper/2504.10147/) (2025)
- [LoRATK: LoRA Once, Backdoor Everywhere in the Share-and-Play Ecosystem](https://mlsanity.com/paper/2403.00108/) (2024)
- [How Far are LLMs from Being Our Digital Twins? A Benchmark for Persona-Based Behavior Chain Simulation](https://mlsanity.com/paper/2502.14642/) (2025)
- [Beware of Your Po! Measuring and Mitigating AI Safety Risks in Role-Play Fine-Tuning of LLMs](https://mlsanity.com/paper/2502.20968/) (2025)
- [EduPlanner: LLM-Based Multi-Agent Systems for Customized and Intelligent Instructional Design](https://mlsanity.com/paper/2504.05370/) (2025)
- [Quantifying and Optimizing Global Faithfulness in Persona-driven Role-playing](https://mlsanity.com/paper/2405.07726/) (2024)
- [Capturing Minds, Not Just Words: Enhancing Role-Playing Language Models with Personality-Indicative Data](https://mlsanity.com/paper/2406.18921/) (2024)
- [Thinking in Character: Advancing Role-Playing Agents with Role-Aware Reasoning](https://mlsanity.com/paper/2506.01748/) (2025)
- [Persistent Personas? Role-Playing, Instruction Following, and Safety in Extended Interactions](https://mlsanity.com/paper/2512.12775/) (2025)
- [MEraser: An Effective Fingerprint Erasure Approach for Large Language Models](https://mlsanity.com/paper/2506.12551/) (2025)
- [LRAgent: Efficient KV Cache Sharing for Multi-LoRA LLM Agents](https://mlsanity.com/paper/2602.01053/) (2026)
- [Does Knowledge Localization Hold True? Surprising Differences Between Entity and Relation Perspectives in Language Models](https://mlsanity.com/paper/2409.00617/) (2024)
- [Revealing and Mitigating the Challenge of Detecting Character Knowledge Errors in LLM Role-Playing](https://mlsanity.com/paper/2409.11726/) (2024)
- [PersonaEval: Are LLM Evaluators Human Enough to Judge Role-Play?](https://mlsanity.com/paper/2508.10014/) (2025)
- [Efficient Multi-Adapter LLM Serving via Cross-Model KV-Cache Reuse with Activated LoRA](https://mlsanity.com/paper/2512.17910/) (2025)
- [The Rise of Darkness: Safety-Utility Trade-Offs in Role-Playing Dialogue Agents](https://mlsanity.com/paper/2502.20757/) (2025)
- [HyCoRA: Hyper-Contrastive Role-Adaptive Learning for Role-Playing](https://mlsanity.com/paper/2511.08017/) (2025)
- [AI Agent Behavioral Science](https://mlsanity.com/paper/2506.06366/) (2025)
- [textttBluePrint: A Social Media User Dataset for LLM Persona Evaluation and Training](https://mlsanity.com/paper/2510.02343/) (2025)
- [Thinking Before Speaking: A Role-playing Model with Mindset](https://mlsanity.com/paper/2409.13752/) (2024)
- [ERABAL: Enhancing Role-Playing Agents through Boundary-Aware Learning](https://mlsanity.com/paper/2409.14710/) (2024)
- [SHARP: Unlocking Interactive Hallucination via Stance Transfer in Role-Playing LLMs](https://mlsanity.com/paper/2411.07965/) (2024)
- [Character-R1: Enhancing Role-Aware Reasoning in Role-Playing Agents via RLVR](https://mlsanity.com/paper/2601.04611/) (2026)
- [Memory-Driven Role-Playing: Evaluation and Enhancement of Persona Knowledge Utilization in LLMs](https://mlsanity.com/paper/2603.19313/) (2026)

## Abstract (arXiv)

Large Language Models (LLMs) have revolutionized open-domain dialogue agents but encounter challenges in multi-character role-playing (MCRP) scenarios. To address the issue, we present Neeko, an innovative framework designed for efficient multiple characters imitation. Unlike existing methods, Neeko employs a dynamic low-rank adapter (LoRA) strategy, enabling it to adapt seamlessly to diverse characters. Our framework breaks down the role-playing process into agent pre-training, multiple characters playing, and character incremental learning, effectively handling both seen and unseen roles. This dynamic approach, coupled with distinct LoRA blocks for each character, enhances Neeko's adaptability to unique attributes, personalities, and speaking patterns. As a result, Neeko demonstrates superior performance in MCRP over most existing methods, offering more engaging and versatile user interaction experiences. Code and data are available at https://github.com/weiyifan1023/Neeko.