Materials science is a field of study that focuses on understanding the properties and performance of various materials, with an emphasis on innovation and the creation of new material for a range of applications. Particular challenges in this field involve integrating large amounts of visual and textual data from scientific literature to enhance material analysis…
Materials science focuses on the study of materials to develop new technologies and improve existing ones. Most researchers in this realm use scientific principles such as physics, chemistry, and understanding of engineering. One major challenge in materials science is collating visual and textual data for analysis to improve material inventions. Traditional methods rarely combine both…
Large Language Models (LLMs) for Information Retrieval (IR) applications, such as those used for web search or question-answering systems, currently base their effectiveness on human-crafted prompts for zero-shot relevance ranking – ranking items by how closely they match the user's query. Manually creating these prompts for LLMs is time-consuming and subjective. Additionally, this method struggles…
In the field of information retrieval (IR), large language models (LLMs) often require human-created prompts for precise relevance ranking. This demands a considerable amount of human effort, increasing the time consumption and subjectivity of the process. Current methods, such as manual prompt engineering, are effective but still time-intensive and plagued by inconsistent skill levels. Current…
Natural language processing plays a crucial role in refining language models for specified tasks by training AI models on vast and detailed datasets. However, the creation of these extensive datasets is arduous and costly, often requiring substantial human effort, and has, thus, resulted in a gap between academic research and industrial applications. The major obstacle…
The Institute for Natural Language Processing (IMS) at the University of Stuttgart, Germany, has made a significant contribution to the field of text-to-speech (TTS) technology with the introduction of ToucanTTS. Supported by PyTorch and Python, ToucanTTS brings to the table a language support encompassing more than 7,000 languages, marking a strong influence on the multilingual…
Safeguarding the ethics and safety of large language models (LLMs) is key to ensuring their use doesn't result in harmful or offensive content. In examining why these models sometimes generate unacceptable text, researchers have discovered that they lack reliable refusal capabilities. Consequently, this paper explores ways in which LLMs can deny certain content types and…
Factory AI has unveiled Code Droid, a major innovation in artificial intelligence (AI) designed to streamline and expedite software development processes. As an autonomous AI tool, Code Droid is created to handle a multitude of coding duties based on natural language instructions, assimilating insights from multiple fields, including robotics, machine learning, and cognitive science.
The key…
Factory AI has launched its state-of-the-art innovation, Code Droid. This artificial intelligence (AI) tool is designed to revolutionize software development by mechanizing and quickening the processes involved. Code Droid is essentially an autonomous system which carries out multiple coding tasks dependent on natural language directions. Its main objective is to automatize mundane programming operations, thus…
The rise of vast data systems has made information retrieval a vital process for numerous platforms, including search engines and recommender systems. This is achieved by finding documents based on their content, a task that presents challenges related to relevance assessment, document ranking, and efficiency. A new Python library named BM25S aims to overcome the…
In the digital era where data is vast, the importance of information retrieval cannot be overstated, particularly for search engines, recommender systems, and applications that find documents based on their content. Information retrieval involves three fundamental challenges - relevance assessment, document ranking, and efficiency. BM25S is a recently introduced Python library that tackles these challenges…
Long-Context Language Models (LCLMs) have emerged as a new frontier in artificial intelligence with the potential to handle complex tasks and applications without needing intricate pipelines that were traditionally used due to the limitations of context length. Unfortunately, their evaluation and development have been fraught with challenges. Most evaluations rely on synthetic tasks with fixed-length…