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19 Nov

From Data Warehousing to Data Intelligence: How Data Took Over

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While GenAI is the focus today, most enterprises have been working for a decade or longer to make data intelligence a reality within their operations.Unified data environments, faster processing speeds, and more robust governance; every improvement was a step forward in helping companies do more with their own information. Now, users of all technical backgrounds have the ability to interact with their private data – whether that’s a business team querying data in natural language or a data scientist being able to quickly and efficiently customize an open source LLM.But the capabilities of data intelligence continue to evolve, and the…

19 Nov

Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration

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[Submitted on 10 Jun 2024 (v1), last revised 16 Nov 2024 (this version, v3)] View a PDF of the paper titled Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration, by Yuanjie Shi and 3 other authors View PDF Abstract:Conformal prediction (CP) is an emerging uncertainty quantification framework that allows us to construct a prediction set to cover the true label with a pre-specified marginal or conditional probability. Although the valid coverage guarantee has been extensively studied for classification problems, CP often produces large prediction sets which may not be practically useful. This issue is exacerbated for the setting…

19 Nov

Gaze-Assisted Medical Image Segmentation

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[Submitted on 23 Oct 2024 (v1), last revised 17 Nov 2024 (this version, v2)] View a PDF of the paper titled Gaze-Assisted Medical Image Segmentation, by Leila Khaertdinova and 3 other authors View PDF HTML (experimental) Abstract:The annotation of patient organs is a crucial part of various diagnostic and treatment procedures, such as radiotherapy planning. Manual annotation is extremely time-consuming, while its automation using modern image analysis techniques has not yet reached levels sufficient for clinical adoption. This paper investigates the idea of semi-supervised medical image segmentation using human gaze as interactive input for segmentation correction. In particular, we fine-tuned…

19 Nov

Estimating the Influence of Sequentially Correlated Literary Properties in Textual Classification: A Data-Centric Hypothesis-Testing Approach

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[Submitted on 7 Nov 2024 (v1), last revised 18 Nov 2024 (this version, v3)] View a PDF of the paper titled Estimating the Influence of Sequentially Correlated Literary Properties in Textual Classification: A Data-Centric Hypothesis-Testing Approach, by Gideon Yoffe and Nachum Dershowitz and Ariel Vishne and Barak Sober View PDF HTML (experimental) Abstract:Stylometry aims to distinguish authors by analyzing literary traits assumed to reflect semi-conscious choices distinct from elements like genre or theme. However, these components often overlap, complicating text classification based solely on feature distributions. While some literary properties, such as thematic content, are likely to manifest as correlations…

19 Nov

Challenges in the Differential Classification of Individual Diagnoses from Co-Occurring Autism and ADHD Using Survey 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

19 Nov

Boundary Attention Constrained Zero-Shot Layout-To-Image Generation

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arXiv:2411.10495v1 Announce Type: new Abstract: Recent text-to-image diffusion models excel at generating high-resolution images from text but struggle with precise control over spatial composition and object counting. To address these challenges, several studies developed layout-to-image (L2I) approaches that incorporate layout instructions into text-to-image models. However, existing L2I methods typically require either fine-tuning pretrained parameters or training additional control modules for the diffusion models. In this work, we propose a novel zero-shot L2I approach, BACON (Boundary Attention Constrained generation), which eliminates the need for additional modules or fine-tuning. Specifically, we use text-visual cross-attention feature maps to quantify inconsistencies between the layout…

19 Nov

Does Prompt Formatting Have Any Impact on LLM Performance?

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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

19 Nov

Automating Unity Catalog Upgrade Workflows with UCX

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As organizations increasingly leverage the Databricks Data Intelligence Platform for data and AI needs, upgrading to Unity Catalog is a key step in enhancing discovery, governance and security to unlock the platform's full potential. UCX, a powerful tool developed by Databricks Labs, simplifies this transition by automating the upgrade process, ensuring a smoother and more efficient journey. In this blog, we'll show how UCX can be a powerful companion as you plan your upgrade journey to Unity Catalog.What is UCX?UCX is an open source Databricks Labs project designed to assist organizations in upgrading their non-Unity Catalog workspaces to Unity Catalog.…

19 Nov

Boolean-aware Boolean Circuit Classification: A Comprehensive Study on Graph Neural Network

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arXiv:2411.10481v1 Announce Type: new Abstract: Boolean circuit is a computational graph that consists of the dynamic directed graph structure and static functionality. The commonly used logic optimization and Boolean matching-based transformation can change the behavior of the Boolean circuit for its graph structure and functionality in logic synthesis. The graph structure-based Boolean circuit classification can be grouped into the graph classification task, however, the functionality-based Boolean circuit classification remains an open problem for further research. In this paper, we first define the proposed matching-equivalent class based on its ``Boolean-aware'' property. The Boolean circuits in the proposed class can be transformed…

19 Nov

Structure Tensor Representation for Robust Oriented Object Detection

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arXiv:2411.10497v1 Announce Type: new Abstract: Oriented object detection predicts orientation in addition to object location and bounding box. Precisely predicting orientation remains challenging due to angular periodicity, which introduces boundary discontinuity issues and symmetry ambiguities. Inspired by classical works on edge and corner detection, this paper proposes to represent orientation in oriented bounding boxes as a structure tensor. This representation combines the strengths of Gaussian-based methods and angle-coder solutions, providing a simple yet efficient approach that is robust to angular periodicity issues without additional hyperparameters. Extensive evaluations across five datasets demonstrate that the proposed structure tensor representation outperforms previous methods…