Unverified50% confidenceFactExact time
The paper notes that proving strict expansion or depth separation requires introducing explicit complexity assumptions, and that under the assumption BPP=P, the randomized classes degenerate into their exact counterparts with the same frontier.
1
Sources
50%
Confidence
Long-term
Relevance
10/9/2026
First Seen
Sources
Related Entities
Related Claims
Unverified分步推理本质上是将复杂条件概率分解为多个较简单条件概率的乘积，降低每步预测难度71% similarUnverifiedPrevious generalization analyses of flow matching/diffusion models often required strong restrictive assumptions on the estimated velocity field, such as global Lipschitz continuity, bounded norm, or specific regularity conditions.69% similarUnverifiedThe guarantees in the HOST paper are established under appropriate conditions, and the robustness of the algorithm to deviations from the Gaussian assumption still requires further exploration.69% similarUnverifiedWriting only one position or conditionally independent positions per step can theoretically match the distribution exactly, while writing more dependent positions causes errors to accumulate.68% similarUnverifiedOpen problems left by the paper include the optimal dependence on the retention probability p (whether the current p^{-9} can be improved) and the precise characterization of logarithmic factors.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/990436API
curl https://kongchang.com/api/v1/knowledge/claims/990436MCP
get_claim(id=990436)