Unverified50% confidenceFactExact time
Khoj's risk score formula is: each path contributes the severity of its label, decaying by distance and the strength of each relationship segment, aggregated into a score similar to Katz centrality, K(p) = Σ over paths P: severity(f) · 0.6^(hops−1) · Π edge weights, and finally score = 100 · (1 − e^(−K)).
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe value of K in Top-K should be determined through offline evaluation by measuring Recall@K at different K values on an annotated test set and finding the inflection point where the recall curve begins to flatten.63% similarUnverifiedKhoj's first version of the risk scoring correctly identified Skyvista Altura but also scored median projects at 94, because contractors and land aggregators acting as hub nodes caused path noise.59% similarUnverifiedKimi K3 is a 2.8T-parameter multimodal LatentMoE model that uses 896 experts with top-16 routing and performs routing computation in a 3584-dimensional latent space.59% similarUnverifiedThe GK summary (Greenwald-Khanna) uses counters with error bounds to provide deterministic approximate guarantees for quantiles.58% similarUnverifiedK-Quant是llama.cpp生态中的混合精度量化方案,根据每层权重敏感度分配不同量化bit数,可在相同平均bit数下将精度损失降低40-60%57% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1062671API
curl https://kongchang.com/api/v1/knowledge/claims/1062671MCP
get_claim(id=1062671)