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Long-context language models (LCLMs) have emerged as a promising technology with the potential to revolutionize artificial intelligence. These models aim to tackle complex tasks and applications while eliminating the need for intricate pipelines that were previously necessary due to context length limitations. However, the development and evaluation of LCLMs face significant challenges. Current evaluation methods…
In the era of vast data, information retrieval is crucial for search engines, recommender systems, and any application that needs to find documents based on their content. The process involves three key challenges: relevance assessment, document ranking, and efficiency. The recently introduced Python library that implements the BM25 algorithm, BM25S addresses the challenge of efficient…
Factory AI has released its latest innovation, Code Droid, a groundbreaking AI tool designed to automate and accelerate software development processes. This release signifies a significant advancement in artificial intelligence and software engineering. Introduction to Code Droid Code Droid is an autonomous system engineered to execute various coding tasks based on natural language instructions. Its…
Ensuring the safety and ethical behavior of large language models (LLMs) in responding to user queries is of paramount importance. Problems arise from the fact that LLMs are designed to generate text based on user input, which can sometimes lead to harmful or offensive content. This paper investigates the mechanisms by which LLMs refuse to…
In the rapidly advancing field of artificial intelligence, one of the most intriguing frontiers is the synthesis of audiovisual content. While video generation models have made significant strides, they often fall short by producing silent films. Google DeepMind is set to revolutionize this aspect with its innovative Video-to-Audio (V2A) technology, which marries video pixels and…
Neural networks, despite their theoretical capability to fit training sets with as many samples as they have parameters, often fall short in practice due to limitations in training procedures. This gap between theoretical potential and practical performance poses significant challenges for applications requiring precise data fitting, such as medical diagnosis, autonomous driving, and large-scale language…
Machine learning has achieved remarkable advancements, particularly in generative models like diffusion models. These models are designed to handle high-dimensional data, including images and audio. Their applications span various domains, such as art creation and medical imaging, showcasing their versatility. The primary focus has been on enhancing these models to better align with human preferences,…
LLMs like ChatGPT and Gemini demonstrate impressive reasoning and answering capabilities but often produce “hallucinations,” meaning they generate false or unsupported information. This problem hampers their reliability in critical fields, from law to medicine, where inaccuracies can have severe consequences. Efforts to reduce these errors through supervision or reinforcement have seen limited success. A subset…
Large Language Models (LLMs) have revolutionized natural language processing, demonstrating exceptional performance on various benchmarks and finding real-world applications. However, the autoregressive training paradigm underlying these models presents significant challenges. Notably, the sequential nature of autoregressive token generation results in slow processing speeds, limiting the models’ efficiency in high-throughput scenarios. Also, this approach can lead…
Roboflow’s Supervision tool is a robust and versatile resource that caters to various computer vision needs. From loading datasets to drawing detections and counting items within a zone, Supervision provides essential functionalities to streamline and enhance these processes. Let’s delve into Supervision’s comprehensive features, installation methods, and practical applications, emphasizing its utility in modern computer…