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[6] [7] At the time, the focus of the research was on improving Seq2seq techniques for machine translation, but the authors go further in the paper, foreseeing the technique's potential for other tasks like question answering and what is now known as multimodal Generative AI. [1] The paper's title is a reference to the song "All You Need Is ...
For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning. [24] In-context learning is an emergent ability [25] of large language models.
Allen Institute for Artificial Intelligence [140] SemOpenAlex: Multidisciplinary SemOpenAlex extends the capabilities of OpenAlex by providing semantic representations of scholarly metadata. It integrates knowledge graph-based features to enhance the discovery of research trends, collaborations, and literature interconnections across all ...
Teachers are turning to AI tools and platforms — such as ChatGPT, Writable, Grammarly and EssayGrader — to assist with grading papers, writing feedback, developing lesson plans and creating ...
English: Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp by Peter Norvig "This is an open-source repository for the book Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp by Peter Norvig (1992), and the code contained therein.
Automated essay scoring (AES) is the use of specialized computer programs to assign grades to essays written in an educational setting. It is a form of educational assessment and an application of natural language processing. Its objective is to classify a large set of textual entities into a small number of discrete categories, corresponding ...
Computing Machinery and Intelligence" is a seminal paper written by Alan Turing on the topic of artificial intelligence. The paper, published in 1950 in Mind, was the first to introduce his concept of what is now known as the Turing test to the general public. Turing's paper considers the question "Can machines think?"
This research investigates a novel approach to language modeling, MambaByte, which departs from the standard token-based methods. Unlike traditional models that rely on breaking text into discrete units, MambaByte directly processes raw byte sequences. This eliminates the need for tokenization, potentially offering several advantages: [8]