24 citations · 70 across the 19 of their papers we have counts for
8 papers · 1 filter
Long-Document Cross-Lingual Summarization
Shaohui Zheng, Zhixu Li, Jiaan Wang +4
Cross-Lingual Summarization (CLS) aims at generating summaries in one language for the given documents in another language. CLS has attracted wide research attention due to its pra…
MMKGR: Multi-hop Multi-modal Knowledge Graph Reasoning
Shangfei Zheng, Weiqing Wang, Jianfeng Qu +3
Multi-modal knowledge graphs (MKGs) include not only the relation triplets, but also related multi-modal auxiliary data (i.e., texts and images), which enhance the diversity of kno…
Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding
Kexuan Xin, Zequn Sun, Wen Hua +3
Entity alignment is a crucial task in knowledge graph fusion. However, most entity alignment approaches have the scalability problem. Recent methods address this issue by dividing…
RT-KGD: Relation Transition Aware Knowledge-Grounded Dialogue Generation
Kexin Wang, Zhixu Li, Jiaan Wang +4
Grounding dialogue system with external knowledge is a promising way to improve the quality of responses. Most existing works adopt knowledge graphs (KGs) as the external resources…
Ensemble Semi-supervised Entity Alignment via Cycle-teaching
Kexuan Xin, Zequn Sun, Wen Hua +4
Entity alignment is to find identical entities in different knowledge graphs. Although embedding-based entity alignment has recently achieved remarkable progress, training data ins…
A Survey on Cross-Lingual Summarization
Jiaan Wang, Fandong Meng, Duo Zheng +4
Cross-lingual summarization is the task of generating a summary in one language (e.g., English) for the given document(s) in a different language (e.g., Chinese). Under the globali…
ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization
Jiaan Wang, Fandong Meng, Ziyao Lu +4
We present ClidSum, a benchmark dataset for building cross-lingual summarization systems on dialogue documents. It consists of 67k+ dialogue documents from two subsets (i.e., SAMSu…
Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks
Jiaan Wang, Beiqi Zou, Zhixu Li +4
Story ending generation is an interesting and challenging task, which aims to generate a coherent and reasonable ending given a story context. The key challenges of the task lie in…