Unverified50% confidenceOpinionExact time
In multi-turn conversations, baseline bias continuously reinforces itself through the model's ongoing reinterpretation of context, with wording biased toward one side being repeatedly cited and amplified, forming inertia.
1
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50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
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Related Claims
UnverifiedWhen a model becomes confused during a multi-turn conversation, stopping the conversation, clearing the context, and consolidating all known information into a single complete single-turn instruction yields noticeably better model performance.75% similarVerifiedIn multi-turn conversations, before each new response is generated, the system must re-input all prior conversation history into the model, causing token consumption to accumulate and grow with each turn75% similarUnverifiedThis prompt template is suitable for redirecting a conversation that has gone off track and for testing a model's robustness.74% similarUnverified在缺乏外部信息注入的封闭循环自我对话中，模型输出会逐渐收敛至固定的表达模式或叙事框架（吸引子状态）72% similarUnverifiedInteractive orchestration strategies (such as multi-model debate and iterative verification) require models to maintain multi-turn conversational context, placing high demands on context window length and computational resources—precisely the two main bottlenecks of SLMs72% similar
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