6 citations · 15 across the 7 of their papers we have counts for
7 papers
Editing Language Model-based Knowledge Graph Embeddings
Siyuan Cheng, Ningyu Zhang, Bozhong Tian +3
Recently decades have witnessed the empirical success of framing Knowledge Graph (KG) embeddings via language models. However, language model-based KG embeddings are usually deploy…
Construction and Applications of Billion-Scale Pre-Trained Multimodal Business Knowledge Graph
Shumin Deng, Chengming Wang, Zhoubo Li +11
Business Knowledge Graphs (KGs) are important to many enterprises today, providing factual knowledge and structured data that steer many products and make them more intelligent. De…
Commonsense Knowledge Salience Evaluation with a Benchmark Dataset in E-commerce
Yincen Qu, Ningyu Zhang, Hui Chen +6
In e-commerce, the salience of commonsense knowledge (CSK) is beneficial for widespread applications such as product search and recommendation. For example, when users search for `…
SQUIRE: A Sequence-to-sequence Framework for Multi-hop Knowledge Graph Reasoning
Yushi Bai, Xin Lv, Juanzi Li +4
Multi-hop knowledge graph (KG) reasoning has been widely studied in recent years to provide interpretable predictions on missing links with evidential paths. Most previous works us…
Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making
Zijun Yao, Chengjiang Li, Tiansi Dong +6
Entity Matching (EM) aims at recognizing entity records that denote the same real-world object. Neural EM models learn vector representation of entity descriptions and match entiti…
Is Multi-Hop Reasoning Really Explainable? Towards Benchmarking Reasoning Interpretability
Xin Lv, Yixin Cao, Lei Hou +4
Multi-hop reasoning has been widely studied in recent years to obtain more interpretable link prediction. However, we find in experiments that many paths given by these models are…
Multiple Generative Models Ensemble for Knowledge-Driven Proactive Human-Computer Dialogue Agent
Zelin Dai, Weitang Liu, Guanhua Zhan
Multiple sequence to sequence models were used to establish an end-to-end multi-turns proactive dialogue generation agent, with the aid of data augmentation techniques and variant…