Unverified50% confidenceBenchmarkExact time
In the "emergent misalignment" scenario, SimpleLoRIF's gradient signal can link unsafe code training data with subsequent broadly harmful behavior, with an AUC as high as 0.865.
1
Sources
50%
Confidence
Long-term
Relevance
10/28/2026
First Seen
Sources
Related Entities
Related Claims
Unverified安全分类器判定阈值的调整会影响误判率与漏判率之间的权衡，即ROC曲线上的工作点移动66% similarUnverifiedEmergent Misalignment refers to the phenomenon where a model, after being fine-tuned in a narrow domain, exhibits behavior contrary to its training objectives on entirely unrelated tasks.65% similarUnverifiedUpgrading to @ai-sdk/voyage@2.0.60 is basically zero-risk, but behavior changes brought by the dependency upgrade (such as retry counts and error classification), while not breaking the API, may still affect runtime behavior in edge cases; in production environments it is recommended to run the existing test cases after upgrading.65% similarUnverifiedStatistical behavioral anomaly signals include a sudden increase in the proportion of code deletion, systematic deviations in cyclomatic complexity, and significant changes in the frequency or type distribution of tool calls.65% similarUnverifiedRLHF微调阶段相比预训练在数据量级上通常小2-3个数量级，使安全行为编码为低秩覆写而非底层重塑65% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1105869API
curl https://kongchang.com/api/v1/knowledge/claims/1105869MCP
get_claim(id=1105869)