6 papers
Con Instruction: Universal Jailbreaking of Multimodal Large Language Models via Non-Textual Modalities
Jiahui Geng, Thy Thy Tran, Preslav Nakov +1
Existing attacks against multimodal language models (MLLMs) primarily communicate instructions through text accompanied by adversarial images. In contrast, we exploit the capabilit…
VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration
Jiahui Geng, Qing Li, Zongxiong Chen +7
The rapid advancement of vision-language models (VLMs) has brought a lot of attention to their safety alignment. However, existing methods have primarily focused on model undersafe…
CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation
Emilio Villa-Cueva, Sholpan Bolatzhanova, Diana Turmakhan +32
Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey…
A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models
Jiahui Geng, Qing Li, Herbert Woisetschlaeger +6
This study investigates the machine unlearning techniques within the context of large language models (LLMs), referred to as \textit{LLM unlearning}. LLM unlearning offers a princi…
GenAI Content Detection Task 1: English and Multilingual Machine-Generated Text Detection: AI vs. Human
Yuxia Wang, Artem Shelmanov, Jonibek Mansurov +23
We present the GenAI Content Detection Task~1 -- a shared task on binary machine generated text detection, conducted as a part of the GenAI workshop at COLING 2025. The task consis…
FIRE: Fact-checking with Iterative Retrieval and Verification
Zhuohan Xie, Rui Xing, Yuxia Wang +5
Fact-checking long-form text is challenging, and it is therefore common practice to break it down into multiple atomic claims. The typical approach to fact-checking these atomic cl…