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Researchers from Stanford and Cornell Introduce APRICOT: A Novel AI Approach that Merges LLM-based Bayesian Active Preference Learning with Constraint-Aware Task Planning

In the rapidly evolving field of household robotics, a significant challenge has emerged in executing personalized organizational tasks, such as arranging groceries in a refrigerator. These tasks require robots to balance user preferences with physical constraints while avoiding collisions and maintaining stability. While Large Language Models (LLMs) enable natural language communication of user preferences, this…

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Open the Artificial Brain: Sparse Autoencoders for LLM Inspection | by Salvatore Raieli | Nov, 2024

|LLM|INTERPRETABILITY|SPARSE AUTOENCODERS|XAI| A deep dive into LLM visualization and interpretation using sparse autoencoders Image created by the author using DALL-EAll things are subject to interpretation whichever interpretation prevails at a given time is a function of power and not truth. — Friedrich Nietzsche As AI systems grow in scale, it is increasingly difficult and pressing…

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The Ultimate Guide to Assessing Table Extraction

Introduction to Table extraction Extracting tables from documents may sound straightforward, but in reality, it is a complex pipeline involving parsing text, recognizing structure, and preserving the precise spatial relationships between cells. Tables carry a wealth of information compacted into a grid of rows and columns, where each cell holds context based on its neighboring…

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Researchers from Bloomberg and UNC Chapel Hill Introduce M3DocRAG: A Novel Multi-Modal RAG Framework that Flexibly Accommodates Various Document Context

Document Visual Question Answering (DocVQA) represents a rapidly advancing field aimed at improving AI’s ability to interpret, analyze, and respond to questions based on complex documents that integrate text, images, tables, and other visual elements. This capability is increasingly valuable in finance, healthcare, and law settings, as it can streamline and support decision-making processes that…

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