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Neurobiological Motivation for Artificial Intelligence: The Long-Term LLM Memory Structure of the HippoRAG Model

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 3, 202468Views0Likes0Comments
The existing language learning models (LLMs) are advancing yet have been struggling with incorporating new knowledge without forgetting the previous information, a situation termed as "catastrophic forgetting." The present methods, such as retrieval-augmented generation (RAG), are not very effective in tasks demanding integration of new knowledge from various passages due to encoding each passage in…

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A Comprehensive Guide: How RAG supports Transformers in creating adaptable Large Language Models

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 2, 202464Views0Likes0Comments
Natural Language Processing (NLP) has undergone a dramatic transformation in recent years, largely due to advanced language models such as transformers. The emergence of Retrieval-Augmented Generation (RAG) is one of the most groundbreaking achievements in this field. RAG integrates retrieval systems with generative models, resulting in versatile, efficient, and accurate language models. However, before delving…

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GNN-RAG: An innovative AI approach that merges language comprehension capabilities of LLMs with the cognitive abilities of GNNs in a retrieval-enhanced generation (RAG) manner.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 2, 202455Views0Likes0Comments
Researchers from the University of Minnesota have developed a new method to strengthen the performance of large language models (LLMs) in knowledge graph question-answering (KGQA) tasks. The new approach, GNN-RAG, incorporates Graph Neural Networks (GNNs) to enable retrieval-augmented generation (RAG), which enhances the LLMs' ability to answer questions accurately. LLMs have notable natural language understanding capabilities,…

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The SEAL Research Lab from Scale AI has introduced LLM Leaderboards evaluated by experts, known for their reliability and trustworthiness.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 2, 202460Views0Likes0Comments
Scale AI's Safety, Evaluations, and Alignment Lab (SEAL) has unveiled SEAL Leaderboards, a novel ranking system designed to comprehensively gauge the trove of large language models (LLMs) becoming increasingly significant in AI developments. Solely conceived to offer fair, systematic evaluations of AI models, the innovatively-designed leaderboards will serve to highlight disparities and compare performance levels…

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Ant Group Introduces MetRag: A Multi-Level Thought-Boosted Retrieval Augmented Generation Structure

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 2, 202468Views0Likes0Comments
Researchers in the field of Artificial Intelligence (AI) have made considerable advances in the development and application of large language models (LLMs). These models are capable of understanding and generating human language, and hold the potential to transform how we interact with machines and handle information-processing tasks. However, one persistent challenge is their performance in…

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Closest Neighbor Conjectural Decoding (NEST): A Revision Technique Applied During Inference-Time in Language Models to Improve Accuracy and Attribution Utilizing Closest Neighbor Conjectural Decoding

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 2, 202459Views0Likes0Comments
Large Language Models (LLMs) are known for their ability to carry out multiple tasks and perform exceptionally across diverse applications. However, their potential to produce accurate information is inhibited, particularly when the knowledge is less represented in their training data. To tackle this issue, a technique known as retrieval augmentation was devised, combining information retrieval…

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Complexity of Data and Growth Rules in Neural Language Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 2, 202472Views0Likes0Comments
Selecting the right balance between enhancing the data set and enhancing the model parameters in a given computational budget is essential for the optimization of Neural Networks. Scaling rules assist in this allocation of strategies. Past research has recognized a 1-to-1 ratio of parameter count scaling and training token count as the most effective approach…

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This AI research conducted by Princeton and the University of Warwick suggests an innovative AI method to improve the use of LLMs as cognitive models.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 2, 202463Views0Likes0Comments
Large Language Models (LLMs) often exhibit judgment and decision-making patterns that resemble those of humans, posing them as attractive candidates for studying human cognition. They not only emulate rational norms such as risk and loss aversion, but also showcase human-like errors and biases, particularly in probability judgments and arithmetic operations. Despite their potential prospects, challenges…

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Flexible Architectural Neural Networks: Employing AI Solutions to Address Symmetric Issues in Optimization of Units and Common Parameters

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 2, 202456Views0Likes0Comments
Researchers from IT University Copenhagen, Denmark have proposed a new approach to solve a challenge with deep neural networks (DNNs) known as the Symmetry Dilemma. This issue arises because standard DNNs have a fixed structure tied to specific dimensions of input and output space. This rigid structure makes it difficult to optimize these networks across…

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Adaptive Visual Tokenization in Matryoshka Multimodal Models: Boosting Efficacy and Versatility in Multimodal Machine Learning

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 2, 202467Views0Likes0Comments
Multimodal machine learning combines various data types such as text, images, and audio to create more accurate and comprehensive models. However, large multimodal models (LMMs), like LLaVA, have been facing problems dealing with high-resolution graphics due to their inflexible and inefficient nature. Many have recognized the necessity for methods that may adjust the number of…

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LLM360 presents K2: An entirely replicate-able, open-source Large Language Model that outperforms Llama 2 70B while using 35% less computational energy.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 2, 202452Views0Likes0Comments
K2 is an advanced large language model (LLM) by LLM360, produced in partnership with MBZUAI and Petuum. This model, dubbed K2-65B, comprises 65 billion parameters and is completely reproducible, meaning that all components, including the code, data, model checkpoints, and intermediate results, are open-source and available to anyone. The main aim of this level of…

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RobustRAG: An Exclusive Protective Structure Designed to Counteract Retrieval Pollution Attacks within Retrieval-Augmented Generation (RAG) Systems.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 2, 202471Views0Likes0Comments
Retrieval-augmented generation (RAG) has been used to enhance the capabilities of large language models (LLMs) by incorporating external knowledge. However, RAG is susceptible to retrieval corruption, a type of attack in which disruptive information is inserted into the document collection, leading to the generation of incorrect or misleading responses. This poses a serious threat to…

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