StorySage: Conversational Autobiography Writing Powered by a Multi-Agent Framework
Shayan Talaei, Meijin Li, Kanu Grover, James Kent Hippler, Diyi Yang, Amin Saberi

TL;DR
StorySage is a multi-agent conversational system that helps users craft personal autobiographies by capturing memories over multiple sessions, improving narrative coherence and user satisfaction.
Contribution
It introduces a novel multi-agent framework for flexible, user-driven autobiography writing, advancing beyond generic conversational assistants.
Findings
Demonstrates effective multi-session memory collection
Improves narrative completeness and flow
Increases user satisfaction in autobiographical writing
Abstract
Every individual carries a unique and personal life story shaped by their memories and experiences. However, these memories are often scattered and difficult to organize into a coherent narrative, a challenge that defines the task of autobiography writing. Existing conversational writing assistants tend to rely on generic user interactions and pre-defined guidelines, making it difficult for these systems to capture personal memories and develop a complete biography over time. We introduce StorySage, a user-driven software system designed to meet the needs of a diverse group of users that supports a flexible conversation and a structured approach to autobiography writing. Powered by a multi-agent framework composed of an Interviewer, Session Scribe, Planner, Section Writer, and Session Coordinator, our system iteratively collects user memories, updates their autobiography, and plans for…
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Taxonomy
TopicsArtificial Intelligence in Games
