116 citations · 246 across the 18 of their papers we have counts for
9 papers · 1 filter
Learning User Representations with Hypercuboids for Recommender Systems
Shuai Zhang, Huoyu Liu, Aston Zhang +6
Modeling user interests is crucial in real-world recommender systems. In this paper, we present a new user interest representation model for personalized recommendation. Specifical…
Uncertainty-Aware Semantic Augmentation for Neural Machine Translation
Xiangpeng Wei, Heng Yu, Yue Hu +3
As a sequence-to-sequence generation task, neural machine translation (NMT) naturally contains intrinsic uncertainty, where a single sentence in one language has multiple valid cou…
CogTree: Cognition Tree Loss for Unbiased Scene Graph Generation
Jing Yu, Yuan Chai, Yujing Wang +2
Scene graphs are semantic abstraction of images that encourage visual understanding and reasoning. However, the performance of Scene Graph Generation (SGG) is unsatisfactory when f…
Cross-modal Knowledge Reasoning for Knowledge-based Visual Question Answering
Jing Yu, Zihao Zhu, Yujing Wang +3
Knowledge-based Visual Question Answering (KVQA) requires external knowledge beyond the visible content to answer questions about an image. This ability is challenging but indispen…
DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue
Xiaoze Jiang, Jing Yu, Yajing Sun +4
Visual Dialogue task requires an agent to be engaged in a conversation with human about an image. The ability of generating detailed and non-repetitive responses is crucial for the…
IIE-NLP-NUT at SemEval-2020 Task 4: Guiding PLM with Prompt Template Reconstruction Strategy for ComVE
Luxi Xing, Yuqiang Xie, Yue Hu +1
This paper introduces our systems for the first two subtasks of SemEval Task4: Commonsense Validation and Explanation. To clarify the intention for judgment and inject contrastive…
On Learning Universal Representations Across Languages
Xiangpeng Wei, Rongxiang Weng, Yue Hu +3
Recent studies have demonstrated the overwhelming advantage of cross-lingual pre-trained models (PTMs), such as multilingual BERT and XLM, on cross-lingual NLP tasks. However, exis…
Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering
Zihao Zhu, Jing Yu, Yujing Wang +3
Fact-based Visual Question Answering (FVQA) requires external knowledge beyond visible content to answer questions about an image, which is challenging but indispensable to achieve…
Multiscale Collaborative Deep Models for Neural Machine Translation
Xiangpeng Wei, Heng Yu, Yue Hu +3
Recent evidence reveals that Neural Machine Translation (NMT) models with deeper neural networks can be more effective but are difficult to train. In this paper, we present a Multi…