49 citations · 101 across the 18 of their papers we have counts for
8 papers · 1 filter
Maximize the Exploration of Congeneric Semantics for Weakly Supervised Semantic Segmentation
Ke Zhang, Sihong Chen, Qi Ju +3
With the increase in the number of image data and the lack of corresponding labels, weakly supervised learning has drawn a lot of attention recently in computer vision tasks, espec…
Semantic Role Labeling as Dependency Parsing: Exploring Latent Tree Structures Inside Arguments
Yu Zhang, Qingrong Xia, Shilin Zhou +3
Semantic role labeling (SRL) is a fundamental yet challenging task in the NLP community. Recent works of SRL mainly fall into two lines: 1) BIO-based; 2) span-based. Despite ubiqui…
MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations
Xinyin Ma, Yong Jiang, Nguyen Bach +4
Entity retrieval, which aims at disambiguating mentions to canonical entities from massive KBs, is essential for many tasks in natural language processing. Recent progress in entit…
DGEM: A New Dual-modal Graph Embedding Method in Recommendation System
Huimin Zhou, Qing Li, Yong Jiang +2
In the current deep learning based recommendation system, the embedding method is generally employed to complete the conversion from the high-dimensional sparse feature vector to t…
Enhanced Universal Dependency Parsing with Automated Concatenation of Embeddings
Xinyu Wang, Zixia Jia, Yong Jiang +1
This paper describes the system used in submission from SHANGHAITECH team to the IWPT 2021 Shared Task. Our system is a graph-based parser with the technique of Automated Concatena…
Towards Emotional Support Dialog Systems
Siyang Liu, Chujie Zheng, Orianna Demasi +5
Emotional support is a crucial ability for many conversation scenarios, including social interactions, mental health support, and customer service chats. Following reasonable proce…
Diversifying Dialog Generation via Adaptive Label Smoothing
Yida Wang, Yinhe Zheng, Yong Jiang +1
Neural dialogue generation models trained with the one-hot target distribution suffer from the over-confidence issue, which leads to poor generation diversity as widely reported in…
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
Xinyu Wang, Yong Jiang, Nguyen Bach +4
Recent advances in Named Entity Recognition (NER) show that document-level contexts can significantly improve model performance. In many application scenarios, however, such contex…