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Fine-Tuning LLM: MEFT Achieves Comparable Performance with Lower Memory Usage through Affordable Training

Large Language Models (LLMs) are complex artificial intelligence tools capable of amazing feats in natural language processing. However, these large models require extensive fine-tuning to adapt to specific tasks, a process that usually involves adjusting a considerable number of parameters and consequently consuming significant computational resources and memory. This means the fine-tuning of LLMs is…

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The Georgia Institute of Technology has produced an AI research paper which presents LARS-VSA (Learning with Abstract RuleS), a Vector Symbolic Framework designed for educating with theoretical regulations.

Analogical reasoning, which enables understanding relationships between objects, is key to abstract thinking in humans. However, machine learning models often struggle with this task, requiring assistance to draw abstract rules from limited data. A process known as the relational bottleneck has been adopted to help rectify this issue, using attention mechanisms to detect correlations between…

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This AI Article by Snowflake assesses the integration of GPT-4 models with OCR and vision technologies to improve text and image analysis: Progressing Document Comprehension.

The field of document understanding, which involves transforming documents into meaningful information, has gained significance with the advent of large language models and increasing use of document images across industries. The primary challenge for researchers in this field, however, is the effective extraction of information from documents that contain a mix of text and visual…

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Progress in AI: Revolutionizing Precision Medicine within Biomedical Field

The confluence of machine learning (ML) and artificial intelligence (AI) with biomedicine has become essential, especially in the field of digital health. The profusion of high-throughput technologies such as genome-wide sequencing, comprehensive medical image libraries, and large-scale drug perturbation screens reveals extensive and intricate biomedical data. By leveraging advanced ML techniques on this multi-omics data,…

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Google AI unveils Proofread, a unique Gboard function that allows effortless corrections at both sentence-level and paragraph-level with just one tap.

Google’s mobile keyboard app, Gboard, uses statistical decoding to counteract the inherent inaccuracies of touch input on small screens, often referred to as the ‘fat finger’ problem. To assist users, Gboard has several features covering word completion, next-word predictions, active auto-correction and active key correction. However, these models do struggle with more complex errors which…

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Stanford researchers propose a two-step model for adjusting the linguistic calibrations of long-form creations.

Large Language Models (LLMs) can sometimes mislead users to make poor decisions by providing wrong information, a phenomenon known as 'hallucination'. To mitigate this, a team of researchers from Stanford University has proposed a new method for linguistic calibration. The new framework involves a two-step training process for LLMs. In the first stage - supervised finetuning…

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Viewing from Diverse Perspectives: The Enhanced Transformer Capabilities of Multi-Head RAG Aids in Better Multi-Faceted Document Search

Retrieval Augmented Generation (RAG) is a method that aids Large Language Models (LLMs) in producing more accurate and relevant data by incorporating a document retrieval system. Current RAG solutions struggle with multi-aspect queries requiring diverse content from multiple documents. Standard techniques like RAPTOR, Self-RAG, and Chain-of-Note focus on data relevance but are not efficient in…

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Striking a Balance Between AI Technology and Conventional Learning: Incorporating Extensive Language Models in Coding Education.

Human-computer interaction (HCI) is the study of how humans interact with computers, with a specific focus on designing innovative interfaces and technologies. One aspect of HCI that has gained prominence is the integration of large language models (LLMs) like OpenAI's GPT models into educational frameworks, specifically undergraduate programming courses. These AI tools have the potential…

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