LLM as a Broken Telephone: Iterative Generation Distorts Information
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 AI-mediated information propagation, raising important questions
about the reliability of LLM-generated content in iterative workflows.
67ca7b557436e6327ca877ff
Amr Mohamed
claimed_verified
2025-03-07T09:09:41.298Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/655efd24afee0e00788bb589/22guLxIWNybbJR3jI-c4w.jpeg
Amr Mohamed
user
amr-mohamed
67ca7b557436e6327ca87800
Mingmeng Geng
admin_assigned
2025-03-07T09:34:23.443Z
67890323f8796231c857231e
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Mingmeng Geng
user
mgeng
67ca7b557436e6327ca87801
Michalis Vazirgiannis
67ca7b557436e6327ca87802
Guokan Shang
claimed_verified
2025-03-07T09:09:38.933Z
6087e598e2b7cc3a117b0dc5
https://cdn-avatars.huggingface.co/v1/production/uploads/6087e598e2b7cc3a117b0dc5/Ctz_W-uo1gOQRBHXalD1P.png
Guokan Shang
user
guokan-shang
LLM as a Broken Telephone: Iterative Generation Distorts Information
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 AI-mediated information propagation, raising important questions
about the reliability of LLM-generated content in iterative workflows.
Large language models distort information through iterative generation, influenced by language choice and chain complexity, with potential implications for AI-mediated information reliability.
large language models iterative generation translation-based experiments