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Zhongyang Li

Harbin Institute of Technology

6 papers hereh-index 8547 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author1
  • last author1

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.AI2
affiliations
  • Harbin Institute of Technology
Homepage
same name
  • Zhongyang Li — 8 papers, h 2
  • Zhongyang Li — 5 papers, h 4
  • Zhongyang Li — 3 papers, h 5
  • Zhongyang Li — 2 papers, h 2
  • Zhongyang Li — 2 papers, h 2
  • Zhongyang Li — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182021
most citedGuided Generation of Cause and Effect

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

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2021★ 52 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.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.CL2019★ 11 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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.