1.2k citations · 3k across the 72 of their papers we have counts for
8 papers · 2 filters
Distilled Dual-Encoder Model for Vision-Language Understanding
Zekun Wang, Wenhui Wang, Haichao Zhu +3
We propose a cross-modal attention distillation framework to train a dual-encoder model for vision-language understanding tasks, such as visual reasoning and visual question answer…
GEDIT: Geographic-Enhanced and Dependency-Guided Tagging for Joint POI and Accessibility Extraction at Baidu Maps
Yibo Sun, Jizhou Huang, Chunyuan Yuan +4
Providing timely accessibility reminders of a point-of-interest (POI) plays a vital role in improving user satisfaction of finding places and making visiting decisions. However, it…
CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervision
Zhongyang Li, Xiao Ding, Kuo Liao +2
Recent work has shown success in incorporating pre-trained models like BERT to improve NLP systems. However, existing pre-trained models lack of causal knowledge which prevents tod…
A Survey on Dialogue Summarization: Recent Advances and New Frontiers
Xiachong Feng, Xiaocheng Feng, Bing Qin
Dialogue summarization aims to condense the original dialogue into a shorter version covering salient information, which is a crucial way to reduce dialogue data overload. Recently…
Language Model as an Annotator: Exploring DialoGPT for Dialogue Summarization
Xiachong Feng, Xiaocheng Feng, Libo Qin +2
Current dialogue summarization systems usually encode the text with a number of general semantic features (e.g., keywords and topics) to gain more powerful dialogue modeling capabi…
DADgraph: A Discourse-aware Dialogue Graph Neural Network for Multiparty Dialogue Machine Reading Comprehension
Jiaqi Li, Ming Liu, Zihao Zheng +4
Multiparty Dialogue Machine Reading Comprehension (MRC) differs from traditional MRC as models must handle the complex dialogue discourse structure, previously unconsidered in trad…
Learning to Share by Masking the Non-shared for Multi-domain Sentiment Classification
Jianhua Yuan, Yanyan Zhao, Bing Qin +1
Multi-domain sentiment classification deals with the scenario where labeled data exists for multiple domains but insufficient for training effective sentiment classifiers that work…
The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey
Yichong Huang, Xiachong Feng, Xiaocheng Feng +1
Recently, various neural encoder-decoder models pioneered by Seq2Seq framework have been proposed to achieve the goal of generating more abstractive summaries by learning to map in…