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Pingbang Hu πŸ‡ΉπŸ‡Ό

@PingbangHu

I work on, with, and for data. Ph.D. candidate @UofIllinois. Fellows @AnthropicAI. Interns @ SIG @amazon @jouhouken. Alumni @Umich @SJTU1896.
Earth pbb.sh Joined July 2021
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Latest posts 5

Pingbang Hu πŸ‡ΉπŸ‡Ό @PingbangHu
It's officially out! We show that pretraining data poisoning for agent is not only possible but practical.
Huge implications on data safety and we are very proud of what we have achieved.

Working on pretraining data gives us lots of insights, fun, and also tears πŸ˜‡ Go check this out!
Xinyan Hu Verified account @xyVickyHu Nov 4
Pretraining data comes from the open internet, where attackers can implant their data. Can 𝐩𝐨𝐒𝐬𝐨𝐧𝐞𝐝 𝐩𝐫𝐞𝐭𝐫𝐚𝐒𝐧𝐒𝐧𝐠 𝐝𝐚𝐭𝐚 π‘π‘œπ‘Ÿπ‘Ÿπ‘’π‘π‘‘ 𝐴𝐼 π‘Žπ‘”π‘’π‘›π‘‘π‘ , even after SFT, RL, and other safety training?

The answer is yes! By controlling even 𝟏/𝟐𝟎𝟎,𝟎𝟎𝟎 of the pretraining data, attackers can backdoor an agent to 𝑒π‘₯𝑒𝑐𝑒𝑑𝑒 π’‚π’“π’ƒπ’Šπ’•π’“π’‚π’“π’š π‘Žπ‘‘π‘‘π‘Žπ‘π‘˜π‘’π‘Ÿ-π‘β„Žπ‘œπ‘ π‘’π‘› π‘π‘œπ‘‘π‘’.

Our new @AnthropicAI Fellows paper: arxiv.org/abs/2610.37741
🧡(1/N)
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Pingbang Hu πŸ‡ΉπŸ‡Ό @PingbangHu
Just add the 4-th column with non-thinking mode and we will see lol
Zeng Jiajun ζ›Ύε˜‰δΏŠ Verified account @zengjiajun_eth Nov 3
> Replicated weight-space programming on my own GPUs today.

> Opus 5.5 edited 2 neuron output columns in layer 29 of Qwen3.5-4B. That is 0.00012% of the weights. No gradients, no training loop.

> Held-out 150 math problems:
> repetition loops 22-25 β†’ 0
> correct 59 β†’ 92-94
> random-patch control: 47-57

> 27 min, $1.03 of API, zero human intervention.
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Pingbang Hu πŸ‡ΉπŸ‡Ό @PingbangHu
interp ppl joke on u who will think opening up a black box model improve capability 😭

joke aside this is very interesting...
Rikiya Takehi @rikiyatakehi Nov 2
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.

We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧡
Blog: rikiyat.github.io/blog/weight-sp…
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