Uncovering Uncontrolled Repetition through Residual Stream Dynamics
Quick summary
arXiv:2609.38802v1 Announce Type: cross Abstract: Uncontrolled repetition can prolong autoregressive generation in large language models (LLMs) and enable resource consumption attacks. Prior analyses of repetitive generation have identified strongly activated features in intermediate and late layers. However, how uncontrolled repetition activity emerges and develops before becoming prominent in these layers remains insufficiently understood. In this paper, we investigate this question primarily in large vision-language models (LVLMs), which support a richer set of uncontrolled repetitions thro
Key takeaways
- arXiv:2609.38802v1 Announce Type: cross Abstract: Uncontrolled repetition can prolong autoregressive generation in large language models (LLMs) and enable resource consumption attacks.
- Prior analyses of repetitive generation have identified strongly activated features in intermediate and late layers.
- However, how uncontrolled repetition activity emerges and develops before becoming prominent in these layers remains insufficiently understood.
Why it matters
“Uncovering Uncontrolled Repetition through Residual Stream Dynamics” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.
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