A deception detection model by using integrated LLM with emotion features.

Traditional lie detection relies on the experience of human interrogators, making it susceptible to subjective factors and leading to misjudgments. To solve this problem, we propose an emotion-enhanced deception detection model, Lie Detection using XGBoost with RoBERTa-based Emotion Features (LieXBerta). In this framework, the Robustly Optimized BERT Pretraining Approach (RoBERTa) is used to extract emotional features from interrogation texts.

Influenza vaccination features revealed by a single-cell transcriptome atlas.

Emerging and re-emerging viruses like influenza virus pose a continuous global public health threat. Vaccines are one of the most effective public health strategies for controlling infectious diseases. However, little is known about the immunological features of vaccination at the single-cell resolution, including for influenza vaccination.