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English(EN) Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement

新指标量化语言模型的“认知疲劳”

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员引入了一个名为疲劳指数（FI）的新指标，用于测量和诊断自回归语言模型中的“认知疲劳”。这种现象以长距离生成过程中性能下降为特征，可能导致文本重复和指令遵循能力丧失。FI 指标不依赖于特定模型且轻量级，它汇集了与提示注意力衰减、表征漂移和熵校准失误相关的信号。在从 1B 到 13B 参数的九个模型上，FI 有效地预测了任务退化和重复现象，揭示了非单调的缩放行为，并确定了加速疲劳发生的因素。 AI

影响 引入了一种新的诊断工具，用于监控和潜在缓解大型语言模型在长文本生成过程中的性能下降。

排序理由 该集群包含一篇学术论文，详细介绍了语言模型中一种新现象的测量和形式化。

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新指标量化语言模型的“认知疲劳”

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该集群包含一篇学术论文，详细介绍了语言模型中一种新现象的测量和形式化。
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Riju Marwah, Ritvik Garimella, Vishal Pallagani, Atishay Jain, Michael Stewart, Amit Sheth ·

    自回归Transformer中的认知疲劳：形式化与测量

    arXiv:2605.30981v1 Announce Type: new Abstract: Autoregressive language models frequently degrade during long-horizon generation, producing repetitive text, losing instruction adherence, and exhibiting unstable entropy. Despite the prevalence of these failures, practitioners lack…

  2. arXiv cs.CL TIER_1 English(EN) · Amit Sheth ·

    自回归 Transformer 中的认知疲劳：形式化与测量

    Autoregressive language models frequently degrade during long-horizon generation, producing repetitive text, losing instruction adherence, and exhibiting unstable entropy. Despite the prevalence of these failures, practitioners lack online diagnostics to detect them in real-time …

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