This article explores the rise of foundation models in time series forecasting. The authors discuss the increasing success of these approaches in areas such as natural language processing and their potential impact on the field of predictive analytics.
Quivr is an open-source RAG framework and a robust AI assistant that helps you manage and interact with information, reducing the burden of information overload. It integrates with all your files and programs, making it easy to find and analyze your data in one place.
The paper proposes a two-phase framework called TnT-LLM to automate the process of end-to-end label generation and assignment for text mining using large language models, where LLMs produce and refine a label taxonomy iteratively using a zero-shot, multi-stage reasoning approach, and are used as data labelers to yield training samples for lightweight supervised classifiers. The framework is applied to the analysis of user intent and conversational domain for Bing Copilot, achieving accurate and relevant label taxonomies and a favorable balance between accuracy and efficiency for classification at scale.
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