activity
20182021
most citedGuided Generation of Cause and Effect

52 citations · 63 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL202152 cited

Guided Generation of Cause and Effect

Zhongyang Li, Xiao Ding, Ting Liu +2

We present a conditional text generation framework that posits sentential expressions of possible causes and effects. This framework depends on two novel resources we develop in th…

cs.CL2019

Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder

Li Du, Xiao Ding, Ting Liu +1

Understanding event and event-centered commonsense reasoning are crucial for natural language processing (NLP). Given an observed event, it is trivial for human to infer its intent…

cs.AI2019

Event Representation Learning Enhanced with External Commonsense Knowledge

Xiao Ding, Kuo Liao, Ting Liu +2

Prior work has proposed effective methods to learn event representations that can capture syntactic and semantic information over text corpus, demonstrating their effectiveness for…

cs.CL2019

Learning to Rank for Plausible Plausibility

Zhongyang Li, Tongfei Chen, Benjamin Van Durme

Researchers illustrate improvements in contextual encoding strategies via resultant performance on a battery of shared Natural Language Understanding (NLU) tasks. Many of these tas…

cs.CL201911 cited

Story Ending Prediction by Transferable BERT

Zhongyang Li, Xiao Ding, Ting Liu

Recent advances, such as GPT and BERT, have shown success in incorporating a pre-trained transformer language model and fine-tuning operation to improve downstream NLP systems. How…

cs.AI2018

Constructing Narrative Event Evolutionary Graph for Script Event Prediction

Zhongyang Li, Xiao Ding, Ting Liu

Script event prediction requires a model to predict the subsequent event given an existing event context. Previous models based on event pairs or event chains cannot make full use…