Customer-obsessed science

Multilingual query localization is integral to modern e-commerce. While machine translation is widely used to translate e-commerce queries, evaluation of query translation in the context of the down-stream search task is overlooked. This study proposes a search ranking-based evaluation framework with an edit-distance based search metric to evaluate machine translation impact on cross-lingual information

Multilingual search is indispensable for a seamless e-commerce experience. E-commerce search engines typically support multilingual search by cascading a machine translation step before searching the index in its primary language. In practice, search query translation usually involves a translation memory matching step before machine translation. A translation memory (TM) can (i) effectively enforce terminologies

Videos often have to be transmitted and stored at low bitrates due to poor network connectivity during adaptive bitrate streaming. Designing optimal bitrate ladders that would select the perceptually-optimized resolution, frame-rate, and compression level for low-bitrate videos for adaptive streaming across the internet is therefore a task of great interest. Towards that end, we conducted the first large-scale

Recent studies have demonstrated the ability of auto-regressive and seq-to-seq generative models to reach state-of-the-art performance on various Natural Language Understanding (NLU) and Natural Language Processing (NLP) tasks. They operate by framing all the tasks in a single formulation: text auto-completion or text-to-text encoding-decoding. These models can be trained on the products corpus in order

In recent years, the dominant paradigm for text spotting is to combine the tasks of text detection and recognition into a single end-to-end framework. Under this paradigm, both tasks are accomplished by operating over a shared global feature map extracted from the input image. Among the main challenges that end-to-end approaches face is the performance degradation when recognizing text across scale variations