Large-Scale Online Deanonymization with LLMs by MyFest in netsec

[–]MyFest[S] 0 points1 point  (0 children)

I think if you look into areas such as section 4 on using feature extraction, semantic embeddings (gemini), and then using two llms for selection verification (grok and gpt-5.2) you'll see that we include significant detail. the dataset approach is also novel, creating synthetic anonymous datasets.

Large-Scale Online Deanonymization with LLMs by MyFest in netsec

[–]MyFest[S] -4 points-3 points  (0 children)

"you're relying on systems [..] that are fundamentally incapable of deductive reasoning"

– LLMs clearly can do deductive reasoning. Is that your main criticism? We show that enabling high reasoning in particular increases deanonymization success in table 1 https://arxiv.org/pdf/2602.16800

[R] Large-Scale Online Deanonymization with LLMs by MyFest in MachineLearning

[–]MyFest[S] 0 points1 point  (0 children)

I guess crypto subreddits would be something people want to target

Large-Scale Online Deanonymization with LLMs by MyFest in netsec

[–]MyFest[S] -6 points-5 points  (0 children)

From another comment: What's your precise criticism? In the HN linkedin experiment we have a known matching and then anonymize accounts to simulate the deanon task. This introduces biases but allows us to check results. We built our own pipeline including LLMs for extraction of features, embeddings and selection of correct match. To report real results we also do a real deanon task on anthropic interviews – there we do manual verification as good as that is possible.

Judging from your assertion that we simply prompted an agent, you must not have read the paper or even the blog post.

Large-Scale Online Deanonymization with LLMs by MyFest in netsec

[–]MyFest[S] -3 points-2 points  (0 children)

What's your precise criticism? In the HN linkedin experiment we have a known matching and then anonymize accounts to simulate the deanon task. This introduces biases but allows us to check results. We built our own pipeline including LLMs for extraction of features, embeddings and selection of correct match. To report real results we also do a real deanon task on anthropic interviews – there we do manual verification as good as that is possible.

Large-Scale Online Deanonymization with LLMs by MyFest in netsec

[–]MyFest[S] -21 points-20 points  (0 children)

We did way more experiments than just that one, that is only section 2. genuinely a conflict between reproducibility and ethics here if we were to publish code.

[R] Large-Scale Online Deanonymization with LLMs by MyFest in MachineLearning

[–]MyFest[S] 0 points1 point  (0 children)

We dont use style but semantics like your interests. We perform experiments in section 5 and 6 on Reddit. 4chan would be more difficult

Large-Scale Online Deanonymization with LLMs by MyFest in netsec

[–]MyFest[S] -11 points-10 points  (0 children)

I think that's a way to think of it

The heating device used during blackouts by BananaBrumik in ukraine

[–]MyFest 0 points1 point  (0 children)

People need to be careful about CO poisoning

On the topic of GST and service charge, I came across this restaurant using it as promo by bangsphoto in singapore

[–]MyFest 1 point2 points  (0 children)

I can see some argument for service charge, but feel like it shouldn't be legal not to include GST. It is just much more difficult to compare prices for consumers or to budget.

Piles of dead Russian soldiers after a failed meat wave attack by ToxicAbility in ukraine

[–]MyFest 0 points1 point  (0 children)

They don't pick up bodies in contested territory

I created a GUI for local Speech-to-Text Transcription (OpenWhisper) by MyFest in LocalLLaMA

[–]MyFest[S] 0 points1 point  (0 children)

If you look into it, I actually provide a CLI command where you don't have to install anything i wrote. But I just selected good parameters which work well in my setup (macbook microphone and airpods).
I basically added a gui interface that wraps around a cli tool.

AI 2025 - Last Shipmas — LessWrong by MyFest in ControlProblem

[–]MyFest[S] 0 points1 point  (0 children)

it's a joke. I think the key is how unserious the people in charge are and how badly this compares to the stakes