10 citations · 17 across the 7 of their papers we have counts for
7 papers
Large Margin Prototypical Network for Few-shot Relation Classification with Fine-grained Features
Miao Fan, Yeqi Bai, Mingming Sun +1
Relation classification (RC) plays a pivotal role in both natural language understanding and knowledge graph completion. It is generally formulated as a task to recognize the relat…
MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search
Miao Fan, Jiacheng Guo, Shuai Zhu +3
Baidu runs the largest commercial web search engine in China, serving hundreds of millions of online users every day in response to a great variety of queries. In order to build a…
S3IM: Stochastic Structural SIMilarity and Its Unreasonable Effectiveness for Neural Fields
Zeke Xie, Xindi Yang, Yujie Yang +5
Recently, Neural Radiance Field (NeRF) has shown great success in rendering novel-view images of a given scene by learning an implicit representation with only posed RGB images. Ne…
A Graph-Guided Reasoning Approach for Open-ended Commonsense Question Answering
Zhen Han, Yue Feng, Mingming Sun
Recently, end-to-end trained models for multiple-choice commonsense question answering (QA) have delivered promising results. However, such question-answering systems cannot be dir…
NL2GDPR: Automatically Develop GDPR Compliant Android Application Features from Natural Language
Faysal Hossain Shezan, Yingjie Lao, Minlong Peng +3
The recent privacy leakage incidences and the more strict policy regulations demand a much higher standard of compliance for companies and mobile apps. However, such obligations al…
Joint learning of object graph and relation graph for visual question answering
Hao Li, Xu Li, Belhal Karimi +2
Modeling visual question answering(VQA) through scene graphs can significantly improve the reasoning accuracy and interpretability. However, existing models answer poorly for compl…
Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction
Mingming Sun, Xu Li, Xin Wang +3
In this paper, we consider the problem of open information extraction (OIE) for extracting entity and relation level intermediate structures from sentences in open-domain. We focus…