Unverified50% confidenceFactExact time
The key engineering constraint of choice questions is that the category system must be closed and complete; if a new category not covered by the training set appears, the model can only force it into a known class, causing misrouting.
1
Sources
50%
Confidence
Long-term
Relevance
10/26/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedFor unknown failure categories, the arbiter must stop rather than automatically inventing a new category.74% similarUnverifiedThe handling of negation by embedding models is a systematic flaw, because mainstream training objectives (masked language modeling, contrastive learning) do not explicitly require the model to distinguish between positive and negative semantics, causing 'like' and 'dislike' to be encoded at nearby positions.72% similarUnverifiedThe pretraining corpora of the vast majority of models are closed-source, forcing membership inference research to rely on heuristic methods to construct members and non-members, which may introduce systematic bias.71% similarUnverified一旦项目脱离Demo阶段进入生产，模型的选择就变得不那么关键，真正困难的是状态管理、失败重试、人工审批、可观测性、权限控制、调试与恢复71% similarUnverifiedExisting training-free self-reflection protocols (generate→critique→revise) operate on flat token streams, so revisions cannot locate which specific step is unreliable, and early stopping cannot exploit structural convergence signals.70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1101573API
curl https://kongchang.com/api/v1/knowledge/claims/1101573MCP
get_claim(id=1101573)