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Getting a good understanding of the user intent is vital for e-commerce applications to surface the right product to a given customer …

Datasets used to train deep learning models in industrial settings often exhibit skewed distributions with some samples repeated a …

Autoregressive decoding limits the efficiency of transformers for Machine Translation (MT). The community proposed specific network …

The rise in loosely-structured data available through text, images, and other modalities has called for new ways of querying them. …

Autoregressive models have achieved impressive results over a wide range of domains in terms of generation quality and downstream task …

Few-shot graph classification is a novel yet promising emerging research field that still lacks the soundness of well-established …

Cross-lingual phenomena are quite common in informal contexts like social media, where users are likely to mix their native language …

3D human pose estimation is fundamental to understanding human behavior. Recently, promising results have been achieved by graph …

Generating shapes using natural language can enable new ways of imagining and creating the things around us. While significant recent …

The 3D cloth segmentation task is particularly challenging due to the extreme variation of shapes, even among the same category of …