VAM! AI Reading Group: Paper "LLMs can hide text in other text of the same length"

​Yunus will present the paper LLMs can hide text in other text of the same length.

​📄 Paper: LLMs can hide text in other text of the same length

​https://arxiv.org/pdf/2510.20075

​To maximize engagement, please try to read the paper in advance.

​Paper 3-line Summary: The paper introduces a rank-based steganography method that lets a large language model hide an arbitrary text perfectly inside another fluent text of the same length. By recording and reusing token ranks in the model’s probability distribution, it achieves full-capacity encoding while keeping the stegotext plausible and human-readable. Experiments on Reddit posts show these stegotexts remain within the normal plausibility range of real text, raising concerns for AI safety, censorship, and trust in language outputs.

​Want to present?

​The list of papers will be available here: https://docs.google.com/spreadsheets/d/1HET5sjnHjwiF3IaCTipR_ZWspfgglqwdBFRWAfKBhp8/edit?usp=sharing

​To connect with the group, join the Discord: https://discord.gg/teJvEejs94

​Timeline:
🕠 6:30 PM – Arrival & Networking.

​🗣️ 6:45 PM ~ 7:15 – Paper Presentation

​🗣️ 7:15 PM - Discussions

​About the Facilitator

​Issam Laradji is a Research Scientist at ServiceNow and an Adjunct Professor at University of British Columbia. He holds a PhD in Computer Science and a PhD from the University of British Columbia, and his research interests include natural language processing, computer vision, and large-scale optimization.

​Looking forward to discussing the latest AI Papers!