| ▲ | JumpCrisscross 2 hours ago | |||||||||||||||||||||||||||||||||||||||||||
> claim is literally worthless without a control group like "industrial control system based in Germany" Like USA and Hong Kong? Or no modifier? The stuff on Table 1? Also, as the study says, “under the null hypothesis that there are no biases affecting code security” geographic modifiers “should not have had any effect.” If adding a geographic modifier causes the model to go haywire (for some modifiers but not others no less), the issue isn’t just at the presentation layer. | ||||||||||||||||||||||||||||||||||||||||||||
| ▲ | anonymous908213 2 hours ago | parent | next [-] | |||||||||||||||||||||||||||||||||||||||||||
> Like USA and Hong Kong? The stuff on Table 1? You mean the stuff they didn't publish any numbers for? > If adding a geographic modifier causes the model to go haywire (for some modifiers but not others no less), the issue isn’t just at the presentation layer. "Introducing irrelevant information causes model performance to degrade" is a completely different claim than "Mentioning Tibet specifically causes model performance to degrade, this must be the result of censorship or intentional sabotage". | ||||||||||||||||||||||||||||||||||||||||||||
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| ▲ | kennywinker 2 hours ago | parent | prev [-] | |||||||||||||||||||||||||||||||||||||||||||
No that’d be in the training data. But it doesn’t indicate intent to censor or sabotage, it could just be that the lack of data involving tibet leads to poorer results. | ||||||||||||||||||||||||||||||||||||||||||||
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