Unverified50% confidenceFactExact time
BETS uses a generative distribution embedding (GDE) to represent the belief at each node and updates it through the POMDP dynamics.
1
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50%
Confidence
Long-term
Relevance
10/14/2026
First Seen
Sources
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Related Claims
UnverifiedA generative distribution embedding (GDE) is a method for representing probability distributions with a parameterized generative model, learning a mapping from low-dimensional latent variables to the state space, while using an encoder to map observation histories to a distribution over latent variables.72% similarUnverifiedBETS relies on the accessibility of the POMDP dynamics to update the belief embedding, and how it applies in scenarios where the dynamics are unknown or difficult to model remains to be explored.63% similarUnverified贝叶斯滤波是POMDP中维护信念状态的核心机制，通过状态转移模型预测先验概率、用观测模型计算似然、归一化得到后验信念63% similarUnverifiedThe core approach of MoPrO-SD is to decompose prompts into functional semantic modules and then sequentially refine these modules using the LLM's own feedback.63% similarUnverifiedGaussian Belief Propagation (GBP) is a distributed inference algorithm that passes messages in graphical models, and its inherently distributed nature makes it well suited for large-scale parallel hardware acceleration.62% similar
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