Dissemination

Automatic Combination of Sample Selection Strategies for Few-Shot Learning In few-shot learning, the selection of samples has a significant impact on the performance of the model. While effective sample selection strategies are well-established in supervised settings, research on large language … Read More

Authorship Attribution in Multilingual Machine-Generated Texts As Large Language Models (LLMs) have reached human-like fluency and coherence, distinguishing machine-generated text (MGT) from human-written content becomes increasingly difficult. While early efforts in MGT detection have focused on binary classification, the growing … Read More

Automated In-the-Wild Data Collection for Continual AI Generated Image Detection The rapid advancement of generative Artificial Intelligence (AI) has introduced significant challenges for reliable AI-generated image detection. Existing detectors often suffer from performance degradation under distribution shifts and when encountering … Read More

MultiCW: A Large-Scale Balanced Benchmark Dataset for Training Robust Check-Worthiness Detection Models Large language models (LLMs) are beginning to reshape how media professionals verify information, yet automated support for detecting check-worthy claims—a key step in the fact-checking process—remains limited. We … Read More

Beyond Speculation: Measuring the Growing Presence of LLM-Generated Texts in Multilingual Disinformation Increased sophistication of large language models (LLMs) and the consequent quality of generated multilingual text raises concerns about potential disinformation misuse. While humans struggle to distinguish LLM-generated content … Read More