Customer-obsessed science


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July 29, 2025New cost-to-serve-software metric that accounts for the full software development lifecycle helps determine which software development innovations provide quantifiable value.
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The proliferation of several streaming services in recent years has now made it possible for a diverse audience across the world to view the same media content, such as movies or TV shows. While translation and dubbing services are being added to make content accessible to the local audience, the support for making content accessible to people with different abilities, such as the Deaf and Hard of Hearing
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2024As e-commerce stores broaden their reach into new regions and introduce new products within established markets, the development of effective machine learning models becomes increasingly challenging due to the scarcity of labeled data. Traditional transfer learning methods typically require some labeled data from the target domain and often face computational bottlenecks. Despite the availability of a few
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2024We present a differentiable rendering framework to learn structured 3D abstractions in the form of primitive assemblies from sparse RGB images capturing a 3D object. By leveraging differentiable volume rendering, our method does not require 3D supervision. Architecturally, our network follows the general pipeline of an image-conditioned neural radiance field (NeRF) exemplified by pixelNeRF for color prediction
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WSDM 20242024While Graph Neural Networks (GNNs) are remarkably successful in a variety of high-impact applications, we demonstrate that, in link prediction, the common practices of including the edges being predicted in the graph at training and/or test have outsized impact on the performance of low-degree nodes. We theoretically and empirically investigate how these practices impact node-level performance across different
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In recent years, Vision Language Models (VLMs) have achieved significant advancements due to the success of large language models. The common strategy for aligning vision and language models involves a two-step process: an alignment (or pretraining) stage and an instruction tuning stage. During the alignment stage, a projection module is trained to map image embeddings into the language space using a paired
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