Unverified50% confidenceFactExact time
Under injection bait, weak models treat the injected incorrect numbers as their own calculation results and fabricate verification processes out of thin air, with the explanatory text appearing consistent with genuine verification, making it impossible to detect errors through auditing.
1
Sources
50%
Confidence
Long-term
Relevance
10/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedError messages should be written for the model to read and must be "actionable" rather than "technically correct" — throwing raw parser errors at the model is of no value.78% similarUnverifiedFlaws in the evaluator interface can masquerade as reasoning failures, and failing to distinguish between the evaluation pipeline and model capability when interpreting benchmark results may lead to misleading conclusions.77% similarUnverifiedSending only the failed node and validation errors rather than the entire generated data stream during retries is the most straightforward subtraction optimization, provided that error information can be precisely localized.77% similarUnverifiedInference methods based on model internal features face a trade-off between false positives and false negatives77% similarUnverified系统会试探性地应用补丁，若失败则将错误信息反馈给模型进行修正，构成闭环纠错机制76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/996778API
curl https://kongchang.com/api/v1/knowledge/claims/996778MCP
get_claim(id=996778)