4 papers
Focusing on Language: Revealing and Exploiting Language Attention Heads in Multilingual Large Language Models
Xin Liu, Qiyang Song, Qihang Zhou +5
Large language models (LLMs) increasingly support multilingual understanding and generation. Meanwhile, efforts to interpret their internal mechanisms have emerged, offering insigh…
Latent Knowledge Scalpel: Precise and Massive Knowledge Editing for Large Language Models
Xin Liu, Qiyang Song, Shaowen Xu +6
Large Language Models (LLMs) often retain inaccurate or outdated information from pre-training, leading to incorrect predictions or biased outputs during inference. While existing…
BadDepth: Backdoor Attacks Against Monocular Depth Estimation in the Physical World
Ji Guo, Long Zhou, Zhijin Wang +4
In recent years, deep learning-based Monocular Depth Estimation (MDE) models have been widely applied in fields such as autonomous driving and robotics. However, their vulnerabilit…
Evaluating Robustness of Large Audio Language Models to Audio Injection: An Empirical Study
Guanyu Hou, Jiaming He, Yinhang Zhou +4
Large Audio-Language Models (LALMs) are increasingly deployed in real-world applications, yet their robustness against malicious audio injection attacks remains underexplored. This…