This study constructed a news article evaluation system that utilizes a language generation model to analyze financial markets. This system enables us to analyze the effect of news articles distributed in financial markets on the stock price of a company. We added the generated news articles as ...
Key features include: comprehensive coverage of both print and online news, including news design and layout, story structure, the role of headlines and leads, style, grammar and vocabularya range of contemporary examples in the international press, from the 2012 ...
However, we were interested only in those functions whose existence was experimentally confirmed, reported in numerous music cultures, secured by a well-established tradition of production and/or consumption, and characterized by objectively recognizable structural features. We did our best to get rid ...
They are particularly effective for entities with distinct contextual cues or entities with features defined in the text. 2. Model-based methods: From a modeling perspective, named entity recognition constitutes a sequence labeling task. In this case, the input to the model is a sequence ...
Adding too many variations of the language can result in errors and might force you to change your language model. To address these issues, the LUIS portal features a Performance Analysis section. You can use this section to understand how your LUIS app is performing when it comes to detecting...
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As one explores the capabilities and advancements in LLMs, they encounter a variety of model variants, each contributing unique features and improvements. The GPT series, developed by OpenAI, is renowned for its proficiency in generating coherent and contextually relevant text. Google’s BERT excels...
The main disadvantages are the need for a new large dataset for every task, the potential for poor generalization out-of-distribution [MPL19], and the potential to exploit spurious features of the training data [GSL+18, NK19], potentially resulting in an unfair comparison with human ...
GLM methods in the section “Aug-Linear text-classification performance” (see Supplementary Table7for a direct comparison). Nevertheless, Aug-Tree models maintain potential advantages, such as storing far fewer parameters, clustering important features together, and better modeling long-range interactions...
features were used to train an Elastic Net model on depression severity, using nested cross-validation. We then tested performance in a held-out test set (30%), comparing predictions of depression versus 8 other aspects of mental health. The depression trained model had modest out-of-sample ...