Unverified50% confidenceSolutionExact time
When testing an agent, real dirty data with typos, colloquialisms, and emotional content should be used, rather than textbook-perfect inputs.
1
Sources
50%
Confidence
Long-term
Relevance
10/5/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedAutomated tools that are prone to false positives may wrongly penalize honest researchers, causing irreversible negative consequences.71% similarUnverifiedAutomated deepfake detection tools are subject to false negatives and false positives and should serve as a supplementary judgment aid rather than an absolute authority.69% similarUnverifiedBoth automatic reference verification and AI-assisted writing carry hallucination risks, as AI may generate citations or statements that appear plausible but are actually incorrect.68% similarUnverifiedAgent类应用因输出为开放式自然语言，缺乏传统模型明确的准确率指标，评估困难67% similarUnverifiedAI trace removal tools may be used to evade AI detection and fabricate originality, raising concerns in the field of academic integrity67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/977752API
curl https://kongchang.com/api/v1/knowledge/claims/977752MCP
get_claim(id=977752)