Edoardo Debenedetti @NeurIPS
@edebenedetti.bsky.social
PhD student at ETH Zurich | Student Researcher at Google | Agents Security and more in general ML Security and Privacy
edoardo.science
spylab.ai
edoardo.science
spylab.ai
Reposted by Edoardo Debenedetti @NeurIPS
I am at NeurIPS 🇨🇦, please reach out if you want to grab a coffee!
December 12, 2024 at 10:36 PM
I am at NeurIPS 🇨🇦, please reach out if you want to grab a coffee!
Reposted by Edoardo Debenedetti @NeurIPS
SPY Lab is in Vancouver for NeurIPS! Come say hi if you see us around 🕵️
December 10, 2024 at 7:43 PM
SPY Lab is in Vancouver for NeurIPS! Come say hi if you see us around 🕵️
I'm in Vancouver for NeurIPS! Feel free to reach out if you wanna meet to chat about security and privacy, especially in the context of LLM agents!
December 10, 2024 at 2:59 PM
I'm in Vancouver for NeurIPS! Feel free to reach out if you wanna meet to chat about security and privacy, especially in the context of LLM agents!
Reposted by Edoardo Debenedetti @NeurIPS
Come do open AI with us in Zurich!
We're hiring PhD students, postdocs (and faculty!)
We're hiring PhD students, postdocs (and faculty!)
Zurich is a great place to live and do research. It became a slightly better one overnight! Excited to see OAI opening an office here with such a great starting team 🎉
Ok, it is yesterdays news already, but good night sleep is important.
After 7 amazing years at Google Brain/DM, I am joining OpenAI. Together with @xzhai.bsky.social and @giffmana.ai, we will establish OpenAI Zurich office. Proud of our past work and looking forward to the future.
After 7 amazing years at Google Brain/DM, I am joining OpenAI. Together with @xzhai.bsky.social and @giffmana.ai, we will establish OpenAI Zurich office. Proud of our past work and looking forward to the future.
December 4, 2024 at 1:49 PM
Come do open AI with us in Zurich!
We're hiring PhD students, postdocs (and faculty!)
We're hiring PhD students, postdocs (and faculty!)
Feel free to recommend @javirandor.com more researchers to add to the list!
I am curating a list of researchers working on AI Safety and Security here go.bsky.app/BcjeVbN.
Reply to this post with your user or other people you think should be included!
Reply to this post with your user or other people you think should be included!
AI Safety and Security
Join the conversation
go.bsky.app
December 4, 2024 at 11:31 AM
Feel free to recommend @javirandor.com more researchers to add to the list!
Reposted by Edoardo Debenedetti @NeurIPS
Apropos of today's Overleaf downtime/slowness: remember to have your files backed up on Github or locally! What if this happened on the day of a conference deadline?
December 3, 2024 at 4:14 PM
Apropos of today's Overleaf downtime/slowness: remember to have your files backed up on Github or locally! What if this happened on the day of a conference deadline?
Reposted by Edoardo Debenedetti @NeurIPS
Anyone may be able to compromise LLMs with malicious content posted online. With just a small amount of data, adversaries can backdoor chatbots to become unusable for RAG, or bias their outputs towards specific beliefs. Check our latest work! 👇🧵
November 25, 2024 at 12:27 PM
Anyone may be able to compromise LLMs with malicious content posted online. With just a small amount of data, adversaries can backdoor chatbots to become unusable for RAG, or bias their outputs towards specific beliefs. Check our latest work! 👇🧵
Reposted by Edoardo Debenedetti @NeurIPS
Ensemble Everything Everywhere is a defense against adversarial examples that people got quite exited about a few months ago (in particular, the defense causes "perceptually aligned" gradients just like adversarial training)
Unfortunately, we show it's not robust...
arxiv.org/abs/2411.14834
Unfortunately, we show it's not robust...
arxiv.org/abs/2411.14834
Gradient Masking All-at-Once: Ensemble Everything Everywhere Is Not Robust
Ensemble everything everywhere is a defense to adversarial examples that was recently proposed to make image classifiers robust. This defense works by ensembling a model's intermediate representations...
arxiv.org
November 25, 2024 at 8:38 AM
Ensemble Everything Everywhere is a defense against adversarial examples that people got quite exited about a few months ago (in particular, the defense causes "perceptually aligned" gradients just like adversarial training)
Unfortunately, we show it's not robust...
arxiv.org/abs/2411.14834
Unfortunately, we show it's not robust...
arxiv.org/abs/2411.14834