activity
20182021
most citedRecent Advances in Neural Question Generation

83 citations · 117 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CL20218 cited

Zero-shot Fact Verification by Claim Generation

Liangming Pan, Wenhu Chen, Wenhan Xiong +2

Neural models for automated fact verification have achieved promising results thanks to the availability of large, human-annotated datasets. However, for each new domain that requi…

cs.CL2020

Exploring Question-Specific Rewards for Generating Deep Questions

Yuxi Xie, Liangming Pan, Dongzhe Wang +2

Recent question generation (QG) approaches often utilize the sequence-to-sequence framework (Seq2Seq) to optimize the log-likelihood of ground-truth questions using teacher forcing…

cs.CL2020

Unsupervised Multi-hop Question Answering by Question Generation

Liangming Pan, Wenhu Chen, Wenhan Xiong +2

Obtaining training data for multi-hop question answering (QA) is time-consuming and resource-intensive. We explore the possibility to train a well-performed multi-hop QA model with…

cs.CL2020

Exploring and Evaluating Attributes, Values, and Structures for Entity Alignment

Zhiyuan Liu, Yixin Cao, Liangming Pan +2

Entity alignment (EA) aims at building a unified Knowledge Graph (KG) of rich content by linking the equivalent entities from various KGs. GNN-based EA methods present promising pe…

cs.CL202020 cited

Multi-modal Cooking Workflow Construction for Food Recipes

Liangming Pan, Jingjing Chen, Jianlong Wu +5

Understanding food recipe requires anticipating the implicit causal effects of cooking actions, such that the recipe can be converted into a graph describing the temporal workflow…

cs.CL20203 cited

Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen

Yixin Cao, Ruihao Shui, Liangming Pan +3

The curse of knowledge can impede communication between experts and laymen. We propose a new task of expertise style transfer and contribute a manually annotated dataset with the g…