awesome llm role playing with persona

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Basic Information

This repository is an open, community-maintained curated bibliography and resource collection focused on role-playing capabilities of large language models with assigned personas. It concentrates on character role-playing such as fictional characters, celebrities, and historical figures and organizes academic papers, datasets, models, benchmarks, blogs, and other materials relevant to persona-driven LLM research. The README groups content into topical areas like characters, demographics, personalization, multi-agent systems, anthropomorphic cognition and social intelligence, and it highlights notable works, trending papers, and recent news. The project documents models and benchmarks referenced in the literature and provides a contribution section and a contributors list to encourage additions. The list is intended to help researchers, practitioners, and developers quickly find and follow developments in the specialized area of persona and role-playing LLMs.

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Features
The repository provides a structured, topical index of papers and resources with annotated lists under headings such as Role-Playing, Characters, Demographics, Personalization, Multi Agents, Anthropomorphic Cognition, Resources, Blogs, and Papers. It highlights must-read and trending works and enumerates benchmarks, datasets and open models mentioned in the literature. The README includes a news log noting accepted papers and important releases, curated examples of influential papers and benchmarks, and pointers to models and leaderboards used in role-playing evaluation. It contains guidance for contributors, a contributors section, and frequent updates to keep the list current. The collection emphasizes empirical studies, benchmarks, datasets, model releases, and evaluation frameworks specifically for persona-based LLM role-play.
Use Cases
This curated list helps researchers, students, and engineers discover and navigate the literature and tools specific to persona-driven and character role-playing with LLMs. It aggregates survey papers, benchmarks, datasets, and example models so readers can identify state-of-the-art methods, evaluation protocols, and recent trends without searching many sources. The organized topical structure makes it easier to find work on personalization, multi-agent interactions, personality and social intelligence evaluations, and synthetic persona generation. News and highlighted entries surface recent conference acceptances and important model releases, aiding literature reviews and comparative evaluations. The contribution instructions and contributor roster enable community growth, making the repository a practical starting point for building experiments, finding datasets or benchmarks, and locating related code and models in this research area.

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