ASIDE accepted to #ICLR2026! 🇧🇷🎉 We architecturally separate instructions and data in LLMs by rotating data token embeddings 90° during the forward pass: one extra matmul, virtually no overhead. Models & code open-sourced ⬇️

✨ 𝗦𝘂𝗯𝗺𝗶𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼: - Quick application - Accepting posters for 2025 papers from top ML / Security venues - 𝗗𝗲𝗮𝗱𝗹𝗶𝗻𝗲: October 28, 2025 - Notifications: October 31, 2025 Submission link: docs.google.com/forms/d/e/1F... Workshop website: llmsafety-unconference.github.io

📢 𝗖𝗮𝗹𝗹 𝗳𝗼𝗿 𝗣𝗼𝘀𝘁𝗲𝗿𝘀: 𝗟𝗟𝗠 𝗦𝗮𝗳𝗲𝘁𝘆 𝗮𝗻𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 @ 𝗘𝗟𝗟𝗜𝗦 𝗨𝗻𝗖𝗼𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 📅 December 2, 2025 📍 Copenhagen An opportunity to discuss your work with colleagues working on similar problems in LLM safety and security

🎉 Excited to announce the Workshop on Foundations of LLM Security at #EurIPS2025! 🇩🇰 Dec 6–7, Copenhagen! 📢 Call for contributed talks is now open! See details at llmsec-eurips.github.io #EurIPS @euripsconf.bsky.social @sahar-abdelnabi.bsky.social @aideenfay.bsky.social @thegruel.bsky.social

Cool news: I have co-affiliated with @floriantramer.bsky.social at @ethz.ch through the #ELLIS PhD program! I will be visiting ETH for the next 3 months to work with @nkristina.bsky.social on LLM Agents Safety.

NeurIPS has decided to do what ICLR did: As a SAC I received the message 👇 This is wrong! If the review process cannot handle so many papers, the conference needs yo split instead of arbitrarily rejecting 400 papers.

Let's push for the obvious solution: Dear @neuripsconf.bsky.social ! Allow authors to present accepted papers at EurIPS instead of NeurIPS rather than just additionally. Likely, at least 500 papers would move to Copenhagen, problem solved.

I will be attending #ACL2025NLP next week in Vienna 🇦🇹 Simply DM me if you want to chat about LLM Safety/Security, especially topics like instruction/data separation and instruction hierarchies.

Are you looking for an opportunity to do curiosity-driven basic ML research after your PhD? Look no further! Apply for a postdoc position in my group at ISTA (ELLIS Unit Vienna)! Topics are flexible, as long as they fit to our general research group's interests, see cvml.ista.ac.at/Postdoc-ML.h...

EurIPS is coming! 📣 Mark your calendar for Dec. 2-7, 2025 in Copenhagen 📅 EurIPS is a community-organized conference where you can present accepted NeurIPS 2025 papers, endorsed by @neuripsconf.bsky.social and @nordicair.bsky.social and is co-developed by @ellis.eu eurips.cc

🚀 We’ve released the source code for 𝗔𝗦𝗜𝗗𝗘 (presented as an 𝗢𝗿𝗮𝗹 at the #ICLR2025 BuildTrust workshop)! 🔍 ASIDE boosts prompt injection robustness without safety-tuning: we simply rotate embeddings of marked tokens by 90° during instruction-tuning and inference. 👇 code & docs👇

I’ll present our 𝗔𝗦𝗜𝗗𝗘 paper as an 𝗢𝗿𝗮𝗹 at the #ICLR2025 BuildTrust workshop! 🚀 ✅ ASIDE = architecturally separating instructions and data in LLMs from layer 0 🔍 +12–44 pp↑ separation, no utility loss​​ 📉 lowers prompt‑injection ASR (without safety tuning!) 🚀 Talk: Hall 4 #6, 28 Apr, 4:45

Tomorrow I am presenting"Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?" at #ICLR2025! Looking forward to fun discussions near the poster! 📆 Sat 26 Apr, 10:00-12:30 - Poster session 5 (#500)

Tomorrow I am presenting"Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?" at #ICLR2025! Looking forward to fun discussions near the poster! 📆 Sat 26 Apr, 10:00-12:30 - Poster session 5 (#500)

I’ll present our 𝗔𝗦𝗜𝗗𝗘 paper as an 𝗢𝗿𝗮𝗹 at the #ICLR2025 BuildTrust workshop! 🚀 ✅ ASIDE = architecturally separating instructions and data in LLMs from layer 0 🔍 +12–44 pp↑ separation, no utility loss​​ 📉 lowers prompt‑injection ASR (without safety tuning!) 🚀 Talk: Hall 4 #6, 28 Apr, 4:45

Landing in Singapore for #ICLR2025 next week! DM me for a 1‑on‑1 about LLM safety, building safe LLMs by design, control and data flows, instruction–data separation and hierarchies. I’m presenting our instruction–data separation paper plus a workshop paper—long post coming.

(1/n) In our #ICLR2025 paper, we explore a fundamental issue that enables prompt injections: 𝐋𝐋𝐌𝐬’ 𝐢𝐧𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐭𝐨 𝐬𝐞𝐩𝐚𝐫𝐚𝐭𝐞 𝐢𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧𝐬 𝐟𝐫𝐨𝐦 𝐝𝐚𝐭𝐚 𝐢𝐧 𝐭𝐡𝐞𝐢𝐫 𝐢𝐧𝐩𝐮𝐭. ✅ Definition of separation 👉 SEP Benchmark 🔍 LLM evals on SEP