AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-Playing (2026.findings-acl)
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| Challenge: | Existing LLMs lack immersion and adaptability, resulting in limited character orchestration and on-the-fly character introduction. |
| Approach: | They propose an LLM-based framework that allows actors to interact with users in an ongoing narrative. |
| Outcome: | The proposed framework outperforms commercial LLMs in character consistency, environment grounding, and narrative coherence. |
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| Challenge: | Existing tools for creating, modifying, and experimenting with interactive dramas are limited. |
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| Challenge: | Existing systems for interactive agents focus on specific capabilities in predetermined scenarios. |
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Zhiheng Xi, Yiwen Ding, Wenxiang Chen, Boyang Hong, Honglin Guo, Junzhe Wang, Xin Guo, Dingwen Yang, Chenyang Liao, Wei He, Songyang Gao, Lu Chen, Rui Zheng, Yicheng Zou, Tao Gui, Qi Zhang, Xipeng Qiu, Xuanjing Huang, Zuxuan Wu, Yu-Gang Jiang
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| Challenge: | aristotle defined drama as a form of storytelling that involves a predefined storyline, emotions and thoughts. |
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| Challenge: | Large Language Model (LLM) agents have demonstrated remarkable capabilities in task automation and intelligent decision-making. |
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| Challenge: | Existing research focuses on character-level settings and static evaluation formats fail to capture the complexity of everyday social interactions. |
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