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23 Aug

CoDi: Conversational Distillation for Grounded Question Answering

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arXiv:2408.11219v1 Announce Type: new Abstract: Distilling conversational skills into Small Language Models (SLMs) with approximately 1 billion parameters presents significant challenges. Firstly, SLMs have limited capacity in their model parameters to learn extensive knowledge compared to larger models. Secondly, high-quality conversational datasets are often scarce, small, and domain-specific. Addressing these challenges, we introduce a novel data distillation framework named CoDi (short for Conversational Distillation, pronounced "Cody"), allowing us to synthesize large-scale, assistant-style datasets in a steerable and diverse manner. Specifically, while our framework is task agnostic at its core, we explore and evaluate the potential of CoDi on the task…

22 Aug

Vectors: Coming to a Database Near You

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(DongIpix/Shutterstock As customers come to grips with the requirements of building and running generative AI applications, they’re finding there’s one important ingredient that makes it all work: a vector database. That’s the number one factor driving adoption of this special type of database. While the sky-high hype around GenAI seems to be wearing off a bit, there is still massive interest in the nascent technology. For instance, a recent Boston Consulting Group survey found that IT leaders are projecting a 30% increase in spending on GenAI and other forms of machine learning in the coming year, while a KPMG survey…

22 Aug

MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data

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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

22 Aug

Adaptive Knowledge Distillation for Classification of Hand Images using Explainable Vision Transformers

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arXiv:2408.10503v1 Announce Type: new Abstract: Assessing the forensic value of hand images involves the use of unique features and patterns present in an individual's hand. The human hand has distinct characteristics, such as the pattern of veins, fingerprints, and the geometry of the hand itself. This paper investigates the use of vision transformers (ViTs) for classification of hand images. We use explainability tools to explore the internal representations of ViTs and assess their impact on the model outputs. Utilizing the internal understanding of ViTs, we introduce distillation methods that allow a student model to adaptively extract knowledge from a teacher…

22 Aug

Reading with Intent

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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

22 Aug

Reality Check for GenAI: Deloitte Finds Enthusiasm Tempered by Adoption Hurdles

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(Jirsak/Shutterstock) A new report by Deloitte reveals that while investment in GenAI is increasing, the clock is ticking to scale and create sustained value. Promising pilots have led to higher investments and rising expectations, however, it has become crucial for GenAI to start providing tangible returns. According to Deloitte, while organizations recognize the potential of GenAI and continue investing in the technology, they are also encountering significant challenges, including integration issues, a shortage of skilled talent, regulatory pressures, and technical difficulties. Gathering insights from over 2,700 business and technology leaders across the globe, Deloitte’s State of Generative AI in the…

22 Aug

What’s new in Workflows?

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Databricks Workflows is the cornerstone of the Databricks Data Intelligence Platform, serving as the orchestration engine that powers critical data and AI workloads for thousands of organizations worldwide. Recognizing this, Databricks continues to invest in advancing Workflows to ensure it meets the evolving needs of modern data engineering and AI projects.This past summer, we held our biggest yet Data + AI Summit, where we unveiled several groundbreaking features and enhancements to Databricks Workflows. Recent updates, announced at the Data + AI Summit, include new data-driven triggers, AI-assisted workflow creation, and enhanced SQL integration, all aimed at improving reliability, scalability, and…

22 Aug

DOMBA: Double Model Balancing for Access-Controlled Language Models via Minimum-Bounded Aggregation

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arXiv:2408.11121v1 Announce Type: new Abstract: The utility of large language models (LLMs) depends heavily on the quality and quantity of their training data. Many organizations possess large data corpora that could be leveraged to train or fine-tune LLMs tailored to their specific needs. However, these datasets often come with access restrictions that are based on user privileges and enforced by access control mechanisms. Training LLMs on such datasets could result in exposure of sensitive information to unauthorized users. A straightforward approach for preventing such exposure is to train a separate model for each access level. This, however, may result in…

22 Aug

GPT-based Textile Pilling Classification Using 3D Point Cloud Data

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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

22 Aug

Combining Objective and Subjective Perspectives for Political News Understanding

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arXiv:2408.11174v1 Announce Type: new Abstract: Researchers and practitioners interested in computational politics rely on automatic content analysis tools to make sense of the large amount of political texts available on the Web. Such tools should provide objective and subjective aspects at different granularity levels to make the analyses useful in practice. Existing methods produce interesting insights for objective aspects, but are limited for subjective ones, are often limited to national contexts, and have limited explainability. We introduce a text analysis framework which integrates both perspectives and provides a fine-grained processing of subjective aspects. Information retrieval techniques and knowledge bases complement…