Summary of A Multi-task Role-playing Agent Capable Of Imitating Character Linguistic Styles, by Siyuan Chen et al.
A Multi-Task Role-Playing Agent Capable of Imitating Character Linguistic Styles
by Siyuan Chen, Qingyi Si, Chenxu Yang, Yunzhi Liang, Zheng Lin, Huan Liu, Weiping Wang
First submitted to arxiv on: 4 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a novel approach to improve Role-Playing Agents (RPAs) by developing StyleRPA, a Multi-Task Role-Playing Agent that can replicate linguistic style and perform tasks beyond multi-turn dialogues. Current RPAs mainly focus on mimicking fundamental attributes while neglecting stylistic replication, resulting in lack of authenticity. The authors created MRstyle, a dataset comprising real individuals with quotations, covering seven tasks (Dialogue, Dictionary, Composition, Story Generation, Product Description, Music Commentary, and Open Question Answering). StyleRPA outperforms recent LLMs and RPAs baselines on these tasks, showcasing its effectiveness in various domains. The code and data will be released. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine having a computer that can pretend to be someone else, like a character from your favorite movie or book. This paper is about making computers better at doing this by creating new training data for these “Role-Playing Agents”. Right now, these agents are pretty good at having conversations, but they don’t really sound like the characters they’re pretending to be. The authors of this paper created a big dataset with lots of quotes from real people and used it to train their agent. This allowed their agent to not only have conversations but also write stories, describe products, and answer questions in different styles. They even released their code and data so others can use them too! |
Keywords
» Artificial intelligence » Multi task » Question answering
