83 citations · 185 across the 24 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
KQA Pro: A Dataset with Explicit Compositional Programs for Complex Question Answering over Knowledge Base
Shulin Cao, Jiaxin Shi, Liangming Pan +6
Complex question answering over knowledge base (Complex KBQA) is challenging because it requires various compositional reasoning capabilities, such as multi-hop inference, attribut…
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…
Semantic Graphs for Generating Deep Questions
Liangming Pan, Yuxi Xie, Yansong Feng +2
This paper proposes the problem of Deep Question Generation (DQG), which aims to generate complex questions that require reasoning over multiple pieces of information of the input…