Healthcare artificial intelligence (AI) is rapidly advancing, with large language models (LLMs) emerging as powerful tools to transform various aspects of clinical practice. These models, capable of understanding and generating human language, are particularly promising in addressing complex medical queries, enhancing patient communication, and supporting clinical decision-making. However, while LLMs have shown remarkable potential across…
Integrating advanced educational technology has opened new avenues for enhancing teaching effectiveness, particularly using large language models (LLMs). These models are increasingly being explored as tools to assist educators, especially those new to teaching, in developing detailed and effective lesson plans. The application of LLMs in education is driven by the potential to generate tailored…
Large language models (LLMs) have made significant strides in various applications, but they continue to face substantial challenges in complex reasoning tasks. For instance, even advanced models like Mistral-7B can only achieve 36.5% accuracy on the GSM8K dataset, despite employing techniques such as Chain-of-Thought (CoT). While fine-tuning has shown promise in improving reasoning capabilities, most…
Transformers are a groundbreaking innovation in AI, particularly in natural language processing and machine learning. Despite their pervasive use, the internal mechanics of Transformers remain a mystery to many, especially those who lack a deep technical background in machine learning. Understanding how these models work is crucial for anyone looking to engage with AI on…
Integrating AI and Human Expertise for Sustainable Agriculture and Forestry: The global shift towards digital transformation is largely driven by advances in AI, particularly statistical ML. AI’s capacity for intelligent analysis, modeling, and management is becoming crucial in sectors like agriculture and forestry, where it aids in the sustainable use and protection of natural resources.…
A new research addresses a critical issue in Multimodal Large Language Models (MLLMs): the phenomenon of object hallucination. Object hallucination occurs when these models generate descriptions of objects not present in the input data, leading to inaccuracies undermining their reliability and effectiveness. For instance, a model might incorrectly assert the presence of a “tie” in…
Optical Character Recognition (OCR) converts text from images into editable data, but it often produces errors due to issues like poor image quality or complex layouts. While OCR technology is valuable for digitizing text, achieving high accuracy can be challenging and typically requires ongoing refinement. Large Language Models (LLMs), such as the ByT5 model, offer…
Deploying large language models (LLMs) has become a significant challenge for developers and researchers. As LLMs grow in complexity and size, ensuring they run efficiently across different platforms, such as personal computers, mobile devices, and servers, is daunting. The problem intensifies when trying to maintain high performance while optimizing the models to fit within the…
Maximum A Posteriori (MAP) decoding is a technique used to estimate the most probable value of an unknown quantity based on observed data and prior knowledge, especially in digital communications and image processing. The effectiveness of MAP decoding depends on the accuracy of the assumed probability model. Researchers from the Nara Institute of Science and…
The research field of log parsing is a critical component of software performance analysis and reliability. It transforms vast amounts of unstructured log data, often spanning hundreds of gigabytes to terabytes daily, into structured formats. This transformation is essential for understanding system execution, detecting anomalies, and conducting root-cause analyses. Traditional log parsers, which rely on…