Staff Archives - Page 74 of 153

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, 202467Views 0Likes 0Comments

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…

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, 202473Views 0Likes 0Comments

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…

Addressing the Issue of Gradient Inversion in Federated Learning: The DAGER Algorithm for Precise Text Reconstruction

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMay 29, 202463Views 0Likes 0Comments

Federated learning is a way to train models collaboratively using data from multiple clients, maintaining data privacy. Yet, this privacy can become compromised by gradient inversion attacks that reconstruct original data from shared gradients. To address this threat and specifically tackle the challenge of text recovery, researchers from INSAIT, Sofia University, ETH Zurich, and LogicStar.ai…

Tracing the Progression of the GPT Series: An In-Depth Examination of Technical Aspects and Performance Indicators from GPT-1 to GPT-4

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMay 29, 202463Views 0Likes 0Comments

Mistral-finetune: A streamlined code structure for resource-effective and high-performing refinements of Mistral’s Models.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedMay 29, 202464Views 0Likes 0Comments

Fine-tuning large language models is a common challenge for many developers and researchers in the AI field. It is a critical process in adapting models to specific tasks or enhancing their performance. But it often necessitates significant computational resources and time. Conventional solutions, such as adjusting all model weights, are resource-intensive, requiring substantial memory and…

NV-Embed: NVIDIA’s Innovative Embedding Model Excels in MTEB Benchmarks

AI Shorts, AI Tool, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedMay 29, 202483Views 0Likes 0Comments

NVIDIA, a leader in artificial intelligence (AI) and graphic processing units (GPUs), has recently launched NV-Embed, an advanced embedding model built on the large language model (LLM) architecture. NV-Embed is set to transform the field of natural language processing (NLP) and has already demonstrated high performance results in the Massive Text Embedding Benchmark (MTEB). Its…

This Artificial Intelligence research study from Cornell University deciphers the intricate factors in estimating interventional probability.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Staff, Tech News, Technology, UncategorizedMay 29, 202460Views 0Likes 0Comments

Causal models play a vital role in establishing the cause-and-effect associations between variables in complex systems, though they struggle to estimate probabilities associated with multiple interventions and conditions. Two main types of causal models have been the focus of AI research - functional causal models and causal Bayesian networks (CBN). Functional causal models make it…

Investigations at Arizona State University Assess ReAct Prompting: The Importance of Similar Examples in Boosting Extensive Language Model Logic

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Staff, Tech News, Technology, UncategorizedMay 29, 202463Views 0Likes 0Comments

Large language models (LLMs) have rapidly improved over time, proving their prowess in text generation, summarization, translation, and question-answering tasks. These advancements have led researchers to explore their potential in reasoning and planning tasks. Despite this growth, evaluating the effectiveness of LLMs in these complex tasks remains a challenge. It's difficult to assess if any performance…

Improving Agent Strategy: A Parametric AI Method for Global Awareness

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMay 28, 202472Views 0Likes 0Comments

Large Language Models (LLMs) have revolutionized natural language processing tasks, and their potential in physical world planning tasks is beginning to be leveraged. However, these models often encounter problems in understanding the actual world, resulting in hallucinatory actions and a reliance on trial-and-error behavior. Researchers have noted that humans perform tasks efficiently by leveraging global…