135 citations · 274 across the 9 of their papers we have counts for
9 papers
WebQA: Multihop and Multimodal QA
Yingshan Chang, Mridu Narang, Hisami Suzuki +3
Scaling Visual Question Answering (VQA) to the open-domain and multi-hop nature of web searches, requires fundamental advances in visual representation learning, knowledge aggregat…
XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation
Yaobo Liang, Nan Duan, Yeyun Gong +21
In this paper, we introduce XGLUE, a new benchmark dataset that can be used to train large-scale cross-lingual pre-trained models using multilingual and bilingual corpora and evalu…
Pre-training Text Representations as Meta Learning
Shangwen Lv, Yuechen Wang, Daya Guo +10
Pre-training text representations has recently been shown to significantly improve the state-of-the-art in many natural language processing tasks. The central goal of pre-training…
The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding
Xiaodong Liu, Yu Wang, Jianshu Ji +8
We present MT-DNN, an open-source natural language understanding (NLU) toolkit that makes it easy for researchers and developers to train customized deep learning models. Built upo…
K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters
Ruize Wang, Duyu Tang, Nan Duan +6
We study the problem of injecting knowledge into large pre-trained models like BERT and RoBERTa. Existing methods typically update the original parameters of pre-trained models whe…
TableQnA: Answering List Intent Queries With Web Tables
Kaushik Chakrabarti, Zhimin Chen, Siamak Shakeri +2
The web contains a vast corpus of HTML tables. They can be used to provide direct answers to many web queries. We focus on answering two classes of queries with those tables: those…
Open Domain Question Answering Using Web Tables
Kaushik Chakrabarti, Zhimin Chen, Siamak Shakeri +1
Tables extracted from web documents can be used to directly answer many web search queries. Previous works on question answering (QA) using web tables have focused on factoid queri…
Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering
Shangwen Lv, Daya Guo, Jingjing Xu +7
Commonsense question answering aims to answer questions which require background knowledge that is not explicitly expressed in the question. The key challenge is how to obtain evid…
Semantic Parsing with Syntax- and Table-Aware SQL Generation
Yibo Sun, Duyu Tang, Nan Duan +6
We present a generative model to map natural language questions into SQL queries. Existing neural network based approaches typically generate a SQL query word-by-word, however, a l…