新闻
Large Language Models Develop Belief State Geometry In-Context
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers found that LLMs develop geometric representations of belief states in their activations, enabling optimal Bayesian prediction from context.
- 为何重要
- Matters for engineers building interpretable LLMs or debugging in-context learning failures in production models.
- 注意
- Study used controlled HMM data and six open-source models; generalization to real-world tasks and closed-source LLMs remains unverified.
- llm
- language model
- prompt
- token
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