Unverified50% confidenceSolutionExact time
Targeted alignment data—supplementing alignment samples specifically tailored to the domains where misalignment occurs—can significantly reduce context confusion.
1
Sources
50%
Confidence
Long-term
Relevance
10/1/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedDenser relevance judgments reduce the probability that correct results retrieved by a model are mistakenly judged as irrelevant, thereby improving evaluation reliability.76% similarUnverified结构化、上下文丰富的提示不仅提升模型输出质量,也能显著降低安全分类器的误触发率76% similarUnverifiedFeeding large amounts of irrelevant code to a model dilutes key information and degrades reasoning quality, so even with large context windows, precise context selection remains critical.76% similarUnverified使用少样本提示词模板时,2-5个高质量、有代表性的示例胜过大量低质量示例,示例的多样性和边界覆盖度比数量更重要76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/964023API
curl https://kongchang.com/api/v1/knowledge/claims/964023MCP
get_claim(id=964023)