11 papers
Beyond Retrieval: Learning Compact User Representations for Scalable LLM Personalization
Heng Cao, Fan Zhang, Jian Yao +8
Personalizing large language models requires adapting model behavior to individual users while preserving robustness and deployment-scale efficiency. Existing approaches typically…
Design Techniques for LLM-Powered Interactive Storytelling: A Case Study of the Dramamancer System
Tiffany Wang, Yuqian Sun, Yi Wang +3
The rise of Large Language Models (LLMs) has enabled a new paradigm for bridging authorial intent and player agency in interactive narrative. We consider this paradigm through the…
Elsewise: Authoring AI-Based Interactive Narrative with Possibility Space Visualization
Yi Wang, John Joon Young Chung, Melissa Roemmele +6
Interactive narrative (IN) authors craft spaces of divergent narrative possibilities for players to explore, with the player's input determining which narrative possibilities they…
LiteraryTaste: A Preference Dataset for Creative Writing Personalization
John Joon Young Chung, Vishakh Padmakumar, Melissa Roemmele +7
People have different creative writing preferences, and large language models (LLMs) for these tasks can benefit from adapting to each user's preferences. However, these models are…
LLMs Behind the Scenes: Enabling Narrative Scene Illustration
Melissa Roemmele, John Joon Young Chung, Taewook Kim +3
Generative AI has established the opportunity to readily transform content from one medium to another. This capability is especially powerful for storytelling, where visual illustr…
Scaffolding Recursive Divergence and Convergence in Story Ideation
Taewook Kim, Matthew Kay, Yuqian Sun +3
Human creative ideation involves both exploration of diverse ideas (divergence) and selective synthesis of explored ideas into coherent combinations (convergence). While processes…