50 citations · 219 across the 30 of their papers we have counts for
9 papers · 1 filter
SgSum: Transforming Multi-document Summarization into Sub-graph Selection
Moye Chen, Wei Li, Jiachen Liu +3
Most of existing extractive multi-document summarization (MDS) methods score each sentence individually and extract salient sentences one by one to compose a summary, which have tw…
A Multimodal Sentiment Dataset for Video Recommendation
Hongxuan Tang, Hao Liu, Xinyan Xiao +1
Recently, multimodal sentiment analysis has seen remarkable advance and a lot of datasets are proposed for its development. In general, current multimodal sentiment analysis datase…
Fine-grained Entity Typing via Label Reasoning
Qing Liu, Hongyu Lin, Xinyan Xiao +3
Conventional entity typing approaches are based on independent classification paradigms, which make them difficult to recognize inter-dependent, long-tailed and fine-grained entity…
DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation
Lijie Wang, Hao Liu, Shuyuan Peng +5
While deep learning models have greatly improved the performance of most artificial intelligence tasks, they are often criticized to be untrustworthy due to the black-box problem.…
Controllable Dialogue Generation with Disentangled Multi-grained Style Specification and Attribute Consistency Reward
Zhe Hu, Zhiwei Cao, Hou Pong Chan +4
Controllable text generation is an appealing but challenging task, which allows users to specify particular attributes of the generated outputs. In this paper, we propose a control…
BASS: Boosting Abstractive Summarization with Unified Semantic Graph
Wenhao Wu, Wei Li, Xinyan Xiao +5
Abstractive summarization for long-document or multi-document remains challenging for the Seq2Seq architecture, as Seq2Seq is not good at analyzing long-distance relations in text.…
Weakly Supervised Dense Video Captioning via Jointly Usage of Knowledge Distillation and Cross-modal Matching
Bofeng Wu, Guocheng Niu, Jun Yu +3
This paper proposes an approach to Dense Video Captioning (DVC) without pairwise event-sentence annotation. First, we adopt the knowledge distilled from relevant and well solved ta…
Syntactic and Semantic-driven Learning for Open Information Extraction
Jialong Tang, Yaojie Lu, Hongyu Lin +4
One of the biggest bottlenecks in building accurate, high coverage neural open IE systems is the need for large labelled corpora. The diversity of open domain corpora and the varie…
Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsing
Kun Wu, Lijie Wang, Zhenghua Li +5
Data augmentation has attracted a lot of research attention in the deep learning era for its ability in alleviating data sparseness. The lack of labeled data for unseen evaluation…