311 citations · 1.1k across the 79 of their papers we have counts for
17 papers · 1 filter
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning
Yujia Qin, Yankai Lin, Ryuichi Takanobu +6
Pre-trained Language Models (PLMs) have shown superior performance on various downstream Natural Language Processing (NLP) tasks. However, conventional pre-training objectives do n…
Rethinking the Promotion Brought by Contrastive Learning to Semi-Supervised Node Classification
Deli Chen, Yankai Lin, Lei Li +4
Graph Contrastive Learning (GCL) has proven highly effective in promoting the performance of Semi-Supervised Node Classification (SSNC). However, existing GCL methods are generally…
Learning from Context or Names? An Empirical Study on Neural Relation Extraction
Hao Peng, Tianyu Gao, Xu Han +5
Neural models have achieved remarkable success on relation extraction (RE) benchmarks. However, there is no clear understanding which type of information affects existing RE models…
Robust Facial Landmark Detection by Cross-order Cross-semantic Deep Network
Jun Wan, Zhihui Lai, Linlin Shen +4
Recently, convolutional neural networks (CNNs)-based facial landmark detection methods have achieved great success. However, most of existing CNN-based facial landmark detection me…
A Sentiment-Controllable Topic-to-Essay Generator with Topic Knowledge Graph
Lin Qiao, Jianhao Yan, Fandong Meng +2
Generating a vivid, novel, and diverse essay with only several given topic words is a challenging task of natural language generation. In previous work, there are two problems left…
MS-Ranker: Accumulating Evidence from Potentially Correct Candidates for Answer Selection
Yingxue Zhang, Fandong Meng, Peng Li +2
As conventional answer selection (AS) methods generally match the question with each candidate answer independently, they suffer from the lack of matching information between the q…
Token-level Adaptive Training for Neural Machine Translation
Shuhao Gu, Jinchao Zhang, Fandong Meng +4
There exists a token imbalance phenomenon in natural language as different tokens appear with different frequencies, which leads to different learning difficulties for tokens in Ne…
ICS-Assist: Intelligent Customer Inquiry Resolution Recommendation in Online Customer Service for Large E-Commerce Businesses
Min Fu, Jiwei Guan, Xi Zheng +6
Efficient and appropriate online customer service is essential to large e-commerce businesses. Existing solution recommendation methods for online customer service are unable to de…
Dual Past and Future for Neural Machine Translation
Jianhao Yan, Fandong Meng, Jie Zhou
Though remarkable successes have been achieved by Neural Machine Translation (NMT) in recent years, it still suffers from the inadequate-translation problem. Previous studies show…
Graph-Based Social Relation Reasoning
Wanhua Li, Yueqi Duan, Jiwen Lu +2
Human beings are fundamentally sociable -- that we generally organize our social lives in terms of relations with other people. Understanding social relations from an image has gre…
Stochastic Low-rank Tensor Bandits for Multi-dimensional Online Decision Making
Jie Zhou, Botao Hao, Zheng Wen +2
Multi-dimensional online decision making plays a crucial role in many real applications such as online recommendation and digital marketing. In these problems, a decision at each t…
Uncertainty-aware Score Distribution Learning for Action Quality Assessment
Yansong Tang, Zanlin Ni, Jiahuan Zhou +4
Assessing action quality from videos has attracted growing attention in recent years. Most existing approaches usually tackle this problem based on regression algorithms, which ign…
Diversifying Dialogue Generation with Non-Conversational Text
Hui Su, Xiaoyu Shen, Sanqiang Zhao +5
Neural network-based sequence-to-sequence (seq2seq) models strongly suffer from the low-diversity problem when it comes to open-domain dialogue generation. As bland and generic utt…
Towards Multimodal Response Generation with Exemplar Augmentation and Curriculum Optimization
Zeyang Lei, Zekang Li, Jinchao Zhang +5
Recently, variational auto-encoder (VAE) based approaches have made impressive progress on improving the diversity of generated responses. However, these methods usually suffer the…
Dense Registration and Mosaicking of Fingerprints by Training an End-to-End Network
Zhe Cui, Jianjiang Feng, Jie Zhou
Dense registration of fingerprints is a challenging task due to elastic skin distortion, low image quality, and self-similarity of ridge pattern. To overcome the limitation of hand…
MAVEN: A Massive General Domain Event Detection Dataset
Xiaozhi Wang, Ziqi Wang, Xu Han +7
Event detection (ED), which means identifying event trigger words and classifying event types, is the first and most fundamental step for extracting event knowledge from plain text…
More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction
Xu Han, Tianyu Gao, Yankai Lin +7
Relational facts are an important component of human knowledge, which are hidden in vast amounts of text. In order to extract these facts from text, people have been working on rel…