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Tong Wang

Amazon Alexa AI

4 papers hereh-index 12443 citations17 works total

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

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
affiliations
  • Amazon Alexa AI
  • University of Massachusetts Boston
Homepage
same name
  • Tong Wang — 25 papers, h 19
  • Tong Wang — 17 papers, h 5
  • Tong Wang — 11 papers, h 4
  • Tong Wang — 8 papers, h 14
  • Tong Wang — 7 papers, h 14
  • Tong Wang — 7 papers, h 14

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

most citedAn Experimental Study of LSTM Encoder-Decoder Model for Text Simplification

35 citations · 62 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CL2017★ 7 cited

Predicting the Quality of Short Narratives from Social Media

Tong Wang, Ping Chen, Boyang Li

An important and difficult challenge in building computational models for narratives is the automatic evaluation of narrative quality. Quality evaluation connects narrative underst…

cs.CL2017

A Semantic QA-Based Approach for Text Summarization Evaluation

Ping Chen, Fei Wu, Tong Wang +1

Many Natural Language Processing and Computational Linguistics applications involves the generation of new texts based on some existing texts, such as summarization, text simplific…

cs.CL2016★ 20 cited

Topic Modeling over Short Texts by Incorporating Word Embeddings

Jipeng Qiang, Ping Chen, Tong Wang +1

Inferring topics from the overwhelming amount of short texts becomes a critical but challenging task for many content analysis tasks, such as content charactering, user interest pr…

cs.CL2016★ 35 cited

An Experimental Study of LSTM Encoder-Decoder Model for Text Simplification

Tong Wang, Ping Chen, Kevin Amaral +1

Text simplification (TS) aims to reduce the lexical and structural complexity of a text, while still retaining the semantic meaning. Current automatic TS techniques are limited to…

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