Latest AI and machine learning research in surveys for healthcare professionals.
Offline evaluation of recommender systems has traditionally treated the problem as a machine learning problem. In the classic case of recommending movies, where the user has provided explicit ratings of which movies they like and don't like, each user's ratings are split into test and train sets, and the evaluation task becomes to predict the held out test data using the training data. This mach...
The proliferation of text-to-image diffusion models (T2I DMs) has led to an increased presence of AI-generated images in daily life. However, biased T2I models can generate content with specific tendencies, potentially influencing people's perceptions. Intentional exploitation of these biases risks conveying misleading information to the public. Current research on bias primarily addresses expli...
Chinese Grammatical Error Correction (CGEC) is a critical task in Natural Language Processing, addressing the growing demand for automated writing a...
There are not one but two dimensions of bias that can be revealed through the study of large AI models: not only bias in training data or the produc...
Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digitised audio biomarkers for disease diagnostics and...
This paper investigates the use of Large Language Models (LLMs) to synthesize public opinion data, addressing challenges in traditional survey metho...
MLLM reasoning has drawn widespread research for its excellent problem-solving capability. Current reasoning methods fall into two types: PRM, which...
With the increasing use of image generation technology, understanding its social biases, including gender bias, is essential. This paper presents th...
Precise perception of the environment is essential in highly automated driving systems, which rely on machine learning tasks such as object detectio...
Integrating large language models (LLMs) like DeepSeek R1 into healthcare requires rigorous evaluation of their reasoning alignment with clinical ex...
Ensuring the reliability and effectiveness of software release decisions is critical, particularly in safety-critical domains like automotive system...
Reliability has become an increasing concern in modern computing. Integrated circuits (ICs) are the backbone of modern computing devices across indu...
Multimodal Retrieval-Augmented Generation (MRAG) enhances large language models (LLMs) by integrating multimodal data (text, images, videos) into re...
This study examines religious biases in AI-generated financial advice, focusing on ChatGPT's responses to financial queries. Using a prompt-based me...
This article reports on the third iteration of a survey of computerized tools and technologies taught as part of postgraduate translation training p...
Investigating the public experience of urgent care facilities is essential for promoting community healthcare development. Traditional survey method...
Small object detection (SOD) is a critical yet challenging task in computer vision, with applications like spanning surveillance, autonomous systems...
Multimodal large language models (MLLMs) have demonstrated significant potential in medical Visual Question Answering (VQA). Yet, they remain prone ...
Diffusion models have demonstrated impressive capabilities in synthesizing diverse content. However, despite their high-quality outputs, these model...
Recent advancements in Large Language Models (LLMs) have led to their increasing integration into human life. With the transition from mere tools to...