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CATS (Contextually Aware Thresholding for Sparsity): A Novel Machine Learning Framework for Inducing and Exploiting Activation Sparsity in LLMs
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Enhancing AI Model’s Scalability and Performance: A Study on Multi-Head Mixture-of-Experts
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Neural Flow Diffusion Models (NFDM): A Novel Machine Learning Framework that Enhances Diffusion Models by Supporting a Broader Range of Forward Processes Beyond the Fixed Linear Gaussian
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Snowflake AI Research Team Unveils Arctic: An Open-Source Enterprise-Grade Large Language Model (LLM) with a Staggering 480B Parameters
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CatLIP: CLIP-level Visual Recognition Accuracy with 2.7× Faster Pre-training on Web-scale Image-Text Data
This paper introduces weakly supervised pre-training of vision models on large-scale image-text data, reframing it as a classification task. This approach eliminates the need for pairwise similarity computations in contrastive loss, addressing computational challenges and achieving a remarkable 2.7% increase in accuracy.
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Bringing the End-User into the AI Picture
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Auto Wiki v2 by Mutable AI: Converting Code into Articles Similar to Wikipedia
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Researchers at NC State University Combines Three-Dimensional Embroidery Techniques with Machine Learning to Create a Fabric-based Sensor that can Control Electronic Devices through Touch
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Researchers at Apple Release OpenELM: Model Improving NLP Efficiency Using Layer-Wise Innovation and Open-Source Approach
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Researchers at ServiceNow Propose a Machine Learning Approach to Deploy a Retrieval Augmented LLM to Reduce Hallucination and Allow Generalization in a Structured Output Task