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Zhoujun Li

32 papers hereh-index 488.7k citations372 works total

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

author position
  • middle author15
  • last author14

Across the 29 of 32 papers where every author was matched, so the position is known.

fields
  • cs.CL20
  • cs.SI4
  • cs.IR2
  • cs.LG2
  • cs.AI1
  • cs.CR1
same name
  • Zhoujun Li — 51 papers, h 19
  • Zhoujun Li — 34 papers, h 17
  • Zhoujun Li — 8 papers, h 4
  • Zhoujun Li — 7 papers
  • Zhoujun Li — 5 papers, h 2
  • Zhoujun Li — 5 papers, h 3

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
20142021
most citedTI-CNN: Convolutional Neural Networks for Fake News Detection

232 citations · 573 across the 32 of their papers we have counts for

collaborators
Showing 2016 · cs.CLShow all

4 papers · 2 filters

cs.CL2016★ 9 cited

Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots

Yu Wu, Wei Wu, Chen Xing +2

We study response selection for multi-turn conversation in retrieval-based chatbots. Existing work either concatenates utterances in context or matches a response with a highly abs…

cs.CL2016★ 29 cited

Knowledge Enhanced Hybrid Neural Network for Text Matching

Yu Wu, Wei Wu, Zhoujun Li +1

Long text brings a big challenge to semantic matching due to their complicated semantic and syntactic structures. To tackle the challenge, we consider using prior knowledge to help…

cs.CL2016★ 8 cited

Detecting Context Dependent Messages in a Conversational Environment

Chaozhuo Li, Yu Wu, Wei Wu +3

While automatic response generation for building chatbot systems has drawn a lot of attention recently, there is limited understanding on when we need to consider the linguistic co…

cs.CL2016★ 11 cited

Response Selection with Topic Clues for Retrieval-based Chatbots

Yu Wu, Wei Wu, Zhoujun Li +1

We consider incorporating topic information into message-response matching to boost responses with rich content in retrieval-based chatbots. To this end, we propose a topic-aware c…

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