Cross-lingual code cloning has become an important and difficult job due to the rising complexity of modern software development, where numerous programming languages are typically employed inside a single project. The term ‘cross-lingual code clone detection’ describes the process of finding identical or nearly identical code segments in several computer languages. Recent advances in Artificial…
To diagnose and cure cancer, pathologic examination of tissue is crucial. The digital versions of the old histological slides used for light microscopy are gradually replacing them with whole-slide images (WSIs). This allows computational pathology to transition from being used primarily as academic proof points to becoming routine tools in clinical practice. To aid in…
Accurate segmentation of structures like cells and organelles is crucial for deriving meaningful biological insights from imaging data. However, as imaging technologies advance, images’ growing size, dimensionality, and complexity present challenges for scaling existing machine-learning techniques. This is particularly evident in volume electron microscopy, such as focused ion beam-scanning electron microscopy (FIB-SEM) with near-isotropic capabilities.…
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…