Saturday, June 15, 2024

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Apple is promising personalized...

At its Worldwide Developer Conference on Monday, Apple for the first time...

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This story originally appeared in The Algorithm, our weekly newsletter on AI....

The data practitioner for...

The rise of generative AI, coupled with the rapid adoption and democratization...
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Evaluating the IWSLT2023 Speech Translation Tasks: Human Annotations, Automatic Metrics, and Segmentation

Human evaluation is a critical component in machine translation system development and has received much attention in text translation research. However, little prior work exists on the topic of human evaluation for speech translation, which adds additional challenges such as noisy data and segmentation mismatches. We take first steps to fill this gap by conducting a comprehensive human evaluation of the results of several shared tasks from the last International Workshop on Spoken Language Translation (IWSLT 2023). We propose an effective evaluation strategy based on automatic resegmentation… Article Source...

Improved Modelling of...

In practice, training using federated learning can be orders of magnitude slower than standard centralized training. This severely limits the amount of experimentation...

IEEE/CVF Conference on...

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024 Article Source link and Credit

Introducing Apple’s On-Device...

Introducing Apple’s On-Device and Server Foundation Models Article Source link and Credit

ContextQ: Generated Questions...

Much of early literacy education happens at home with caretakers reading books to young children. Prior research demonstrates how having dialogue with children...

On Efficient and...

Annotated data is an essential ingredient to train, evaluate, compare and productionalize machine learning models. It is therefore imperative that annotations are of...

Swallowing the Bitter...

We present a novel way to predict molecular conformers through a simple formulation that sidesteps many of the heuristics of prior works and...

KPConvX: Modernizing Kernel...

In the field of deep point cloud understanding, KPConv is a unique architecture that uses kernel points to locate convolutional weights in space,...

Efficient Diffusion Models...

Transformers have demonstrated impressive performance on class-conditional ImageNet benchmarks, achieving state-of-the-art FID scores. However, their computational complexity increases with transformer depth/width or the...

ODGEN: Domain-specific Object...

Modern diffusion-based image generative models have made significant progress and become promising to enrich training data for the object detection task. However, the...