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Penelope: Localized Latent Recurrence for Efficient Structured Reasoning
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Penelope is a framework that performs structured reasoning inside transformer decoder layers using localized recurrent computation instead of visible chain-of-thought tokens.
- 为何重要
- Matters for engineers optimizing inference latency and cost on reasoning tasks where chain-of-thought expansion significantly increases output length.
- 注意
- Results shown on open-source benchmarks only. Unclear how well latent reasoning generalizes to domains beyond structured reasoning or to different model scales.
收听本摘要
- language model
- reasoning
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