Complex Human Activity Recognition (CHAR) in ubiquitous computing, particularly in smart environments, presents significant challenges due to the labor-intensive and error-prone process of labeling datasets with precise temporal information of atomic activities. This task becomes impractical in real-world scenarios where accurate and detailed labeling is scarce. The need for effective CHAR methods that do not… →

In a recent study by Innodata, various large language models (LLMs) such as Llama2, Mistral, Gemma, and GPT were benchmarked for their performance in factuality, toxicity, bias, and propensity for hallucinations. The research introduced fourteen novel datasets designed to evaluate the safety of these models, focusing on their ability to produce factual, unbiased, and appropriate… →

Large language models (LLMs) have demonstrated remarkable performance across various tasks, with reasoning capabilities being a crucial aspect of their development. However, the key elements driving these improvements remain unclear. Currently, the primary approaches to enhance reasoning involve increasing model size and expanding context length through techniques like chain of thought, retrieval augmented generation, and… →

VLMs like LLaVA-Med have advanced significantly, offering multi-modal capabilities for biomedical image and data analysis, which could aid radiologists. However, these models face challenges, such as hallucinations and imprecision in responses, leading to potential misdiagnoses. With radiology departments experiencing increased workloads and radiologists facing burnout, the need for tools to mitigate these issues is pressing.… →

Formal verification is crucial in software engineering to ensure program correctness through mathematical proof. One widely used technique for this purpose is bounded model checking (BMC), which involves verifying the correctness of a program within specified bounds. Python, a programming language favored for its simplicity and extensive libraries, particularly in fields like web development, image… →

Multilingual natural language processing (NLP) is a rapidly advancing field that aims to develop language models capable of understanding & generating text in multiple languages. These models facilitate effective communication and information access across diverse linguistic backgrounds. This field’s importance lies in its potential to bridge the gap between different language speakers, making technological advancements… →