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cs.CR2026
Watermarking for Byzantine Robust LLM Training
Leixu Huang, Zedian Shao, Teodora Baluta
LLM watermarking has emerged as a promising approach for detecting downstream model misuse in centralized settings, but extending it to federated learning (FL) presents unique chal…
cs.CR2026
Cordyceps: Covert Control Attacks on LLMs via Data Poisoning
Zedian Shao, Charles Fleming, Teodora Baluta
Large language models (LLMs) are often fine-tuned on uncurated text datasets that adversaries can poison. Existing poisoning attacks primarily rely on fixed trigger phrases that de…
cs.CV2026
Leave My Images Alone: Preventing Multi-Modal Large Language Models from Analyzing Images via Visual Prompt Injection
Zedian Shao, Hongbin Liu, Yuepeng Hu +1
Multi-modal large language models (MLLMs) have emerged as powerful tools for analyzing Internet-scale image data, offering significant benefits but also raising critical safety and…