5 accepted papers
Dialogue agents powered by Large Language Models (LLMs) show superior performance in various tasks. Despite the better user understanding and human-like responses, their **lack of controllability** remains a key challenge, often leading to unfocused conversations or task failure. To address this, we…
With the rapid development of large language models (LLMs) in math reasoning, the accuracy of models on existing math benchmarks has gradually approached 90% or even higher. More challenging math benchmarks are hence urgently in need to satisfy the increasing evaluation demands. To bridge this gap,
Automatic deep learning-based classification of respiratory sounds is important for the diagnosis of lung diseases. In recent years, many researchers have used pre-trained models to learn more comprehensive features of respiratory sounds. However, as the models become larger, the challenges of long…
Large language models (LLMs) and small language models (SLMs) are being adopted at remarkable speed, although their safety still remains a serious concern. With the advent of multilingual S/LLMs, the question now becomes a matter of scale: can we expand multilingual safety evaluations of these model…
License plate recognition (LPR) plays an important role in intelligent transport systems. The existed LPR systems are mostly based on hand-crafted methods for detection, segmentation, and recognition, which cannot accurately recognize the license plate in unconstrained surveillance environments. In…