Mirror, Mirror on the Wall: Prompt Echoing in Small Instruct Language Models
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Abstract (arXiv)
Prompt echoing is a recognized failure mode of instruct language models, in which a model instead of generating a response, mirrors the provided prompt, even though it did not receive a specific instruction to do so. Is this phenomenon a sign of the model leaking the content of its training dataset, or is it rather caused by a misaligned behavior of the internal induction/copying mechanisms? We investigate prompt echoing small language models from different families (Gemma, Llama, Qwen, SmolLM and OLMo) and show that echoing prompts are likely to have partial overlap with the training dataset but the phenomenon is primarily driven by the model's induction heads.
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References · 8
- 2024The Llama 3 Herd of Modelscited by 14,715
- 2020Extracting Training Data from Large Language Modelscited by 2,189
- 2024OLMo: Accelerating the Science of Language Modelscited by 613
- 2022Rethinking the Role of Scale for In-Context Learning: An Interpretability-based Case Study at 66 Billion Scalecited by 64
- 2024Induction Heads as an Essential Mechanism for Pattern Matching in In-context Learningcited by 46
- 2025Prompt Repetition Improves Non-Reasoning LLMscited by 27
- 2023EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learningcited by 13
- 2026Echoes as Anchors: Probabilistic Costs and Attention Refocusing in LLM Reasoningcited by 2
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