Year: 2025
Type: conference-paper
Abstract: As large language models are increasingly responsible for online content, concerns arise about the impact of repeatedly processing their own outputs.Inspired by the "broken telephone" effect in chained human communication, this study investigates whether LLMs similarly distort information through iterative generation.Through translation-based experiments, we find that distortion accumulates over time, influenced by language choice and chain complexity.While degradation is inevitable, it can be mitigated through strategic prompting techniques.These findings contribute to discussions on the long-term effects of AImediated information propagation, raising important questions about the reliability of LLMgenerated content in iterative workflows.
Institution: École Polytechnique
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4412945528