Understanding and mitigating hallucinations in vision-language models (VLVMs) is an emerging field of research that addresses the generation of coherent but factually incorrect responses by these advanced AI systems. As VLVMs increasingly integrate text and visual inputs to generate responses, the accuracy of these outputs becomes crucial, especially in settings where precision is paramount, such… →

Maritime transportation has always been pivotal for global trade and travel, but navigating the vast and often unpredictable waters presents significant challenges. The advent of autonomous ships promises to revolutionize this domain, leveraging advanced sensors and Artificial Intelligence (AI) to enhance situational awareness and ensure safe navigation. The comprehensive integration of various sensor technologies with… →

The power of LLMs to generate coherent and contextually appropriate text is impressive and valuable. However, these models sometimes produce content that appears accurate but is incorrect or irrelevant—a problem known as “hallucination.” This issue can be particularly problematic in fields requiring high factual accuracy, such as medical or financial applications. Therefore, there’s a pressing… →

Discover the best AI Fraud Prevention Tools and Software for detecting payment fraud, identifying identity theft, preventing insurance fraud, addressing cybersecurity threats, combating e-commerce fraud, and reducing banking and financial fraud. Greip Greip is an AI-powered fraud protection tool that assists developers in protecting their app’s financial security by avoiding payment fraud. Greip provides an… →

Structured commonsense reasoning in natural language processing involves automated generating and manipulating reasoning graphs from textual inputs. This domain focuses on enabling machines to understand and reason about everyday situations as humans would, translating natural language into interconnected concepts that mirror human logical processes. One of the fundamental challenges in this field is the difficulty… →

Information extraction (IE) is a pivotal area of artificial intelligence that transforms unstructured text into structured, actionable data. Despite their expansive capacities, traditional large language models (LLMs) often fail to comprehend and execute the nuanced directives required for precise IE. These challenges primarily manifest in closed IE tasks, where a model must adhere to stringent,… →

The robotics field has historically vacillated between two primary architectural paradigms: modular hierarchical policies and end-to-end policies. Modular hierarchies employ rigid layers such as symbolic planning, trajectory generation, and tracking, while end-to-end policies utilize high-capacity neural networks to map sensory input directly to actions. The emergence of large language models (LLMs) has renewed interest in… →

In medical technology, developing and utilizing large language models (LLMs) are increasingly pivotal. These advanced models can digest and interpret vast quantities of medical texts, offering insights that traditionally require extensive human expertise. The evolution of these technologies holds the potential to lower healthcare costs significantly and expand access to medical knowledge across various demographics.… →