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Improving Answer Selection in Community Question Answering using Question-Answer Cross Attention Networks (QAN)

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMay 30, 202435Views0Likes0Comments
Community Question Answering (CQA) platforms like Quora, Yahoo! Answers, and StackOverflow are popular online forums for information exchange. However, due to the variable quality of responses, users often struggle to sift through myriad answers to find pertinent information. Traditional methods of answer selection in these platforms include content/user modeling and adaptive support. Still, there's room…

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Healthcare Deep Learning: Obstacles, Uses, and Prospective Pathways

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedMay 29, 202435Views0Likes0Comments
Biomedical data is increasingly complex, spanning various sources such as electronic health records (EHRs), imaging, omics data, sensors, and text. Traditional data mining and statistical methods struggle to extract meaningful insights from this high-dimensional, heterogeneous data. Recent advancements in deep learning offer a transformative solution, enabling models that can directly process raw biomedical data. Such…

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The Emergence of Retrieval-Augmented Generation (RAG) in AI: The Ascend in Artificial Intelligence

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, RAG, Staff, Tech News, Technology, UncategorizedMay 29, 202435Views0Likes0Comments
Artificial Intelligence (AI) and data science are fast-growing fields, with the development of Agentic Retrieval-Augmented Generation (RAG), a promising evolution that seeks to improve how information is utilized and managed compared to current RAG systems. Retrieval-augmented generation (RAG) refines large language model (LLM) applications through the use of bespoke data. By consulting external authoritative knowledge bases…

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Understanding Feature Representation: Examining Inductive Biases in Deep Learning

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Deep Learning, Editors Pick, Staff, Tech News, Technology, UncategorizedMay 29, 202442Views0Likes0Comments
Research conducted by DeepMind has shed new light on the complexities of machine learning and neural representation, providing insights into the dissociations between representation and computation in deep networks. High capacity deep networks frequently demonstrate an implicit bias towards simplicity amidst their learning dynamics and structure. The employed simple functions allow for easier learning of…

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The Research Group of InternLM has launched InternLM2-Math-Plus which is an array of Math-Centric LLMs available in various sizes like 1.8B, 7B, 20B, and 8x22B. They offer improved thought chaining, code understanding, and reasoning capabilities based on LEAN 4.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedMay 29, 202434Views0Likes0Comments
The InternLM research team is dedicated to improving and developing large language models (LLMs) specifically tailored for mathematical reasoning and problem-solving. They aim to strengthen artificial intelligence's performance ability when dealing with mathematically complex tasks, such as formal proofs and informal problem-solving. Researchers from several esteemed institutions have worked together on producing the InternLM2-Math-Plus model…

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The Transformation in AI-Based Image Creation: DALL-E, CLIP, VQ-VAE-2, and ImageGPT

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMay 29, 202445Views0Likes0Comments
Artificial Intelligence (AI) has witnessed significant breakthroughs in image generation in recent years with four models, DALL-E, CLIP, VQ-VAE-2, and ImageGPT, emerging as game-changers in this space. DALL-E, a variant of the GPT-3 model, is designed to generate images from textual descriptions. Taking its name from surrealist Salvador Dalí and Pixar’s WALL-E, DALL-E boasts creative skills…

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Pandora: A Combined Autoregressive-Diffusion Model that Creates Global State Simulations through Video Production and Offers Immediate Control through Unstructured Text Actions

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMay 29, 202438Views0Likes0Comments
An AI's understanding and reproduction of the natural world are based on its 'world model' (WM), a simplified representation of the environment. This model includes objects, scenarios, agents, physical laws, temporal and spatial information, and dynamic interactions, allowing the AI to anticipate reactions to certain actions. The versatility of a world model lends itself extremely…

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Leading AI Programs by NVIDIA

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedMay 29, 202433Views0Likes0Comments
With the advancement of AI across various industries, NVIDIA leads the way through the provision of innovative technologies and solutions. Notably, NVIDIA offers a broad range of AI courses, designed to equip learners with the expertise needed to fully tap into AI's potential. These courses provide in-depth training on advanced subjects such as generative AI,…

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A new multi-scale framework named Hierarchical Graph Masked AutoEncoders (Hi-GMAE) is designed to manage the hierarchical structures inherent in the graph.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMay 29, 202434Views0Likes0Comments
The traditional methods of supervised learning often encounter difficulties when applied to graph analysis as they require labeled data, which is complex and challenging in the case of academic, social, and biological networks. Graph Self-supervised Pre-training (GSP) techniques, classified broadly as contrastive and generative, address these limitations by harnessing the inherent structures and features of…

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Hierarchical Graph Masked AutoEncoders (Hi-GMAE): An Innovative Multi-Level GMAE Structure Engineered to Manage the Hierarchical Configurations within a Graph.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMay 29, 202442Views0Likes0Comments
In graph analysis, collecting labeled data for traditional supervised learning methods can be challenging, particularly for academic, social, and biological networks. As a means to navigate this, Graph Self-supervised Pre-training (GSP) techniques have become more prevalent. These methods capitalize on the inherent structures and characteristics of graph data, mining meaningful representations without needing labeled examples…

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