Yequan Wang (王业全)

Yequan Wang (王业全)

Researcher of Artificial Intelligence

Beijing Academy of Artificial Intelligence (BAAI)

Biography

Dr. Wang Yequan is a researcher at Beijing Academy of Artificial Intelligence (BAAI). His research interests include pre-trained language model, dialog model and sentiment analysis. He leads the Recognition and Data group, which develops large-scaled language foundation model, data centric AI and industry foundation model.

From Sep. 2017 to Sep. 2018, Dr. Wang studied at Nanyang Technological University as a Joint Ph.D. Candidate, supervised by Associate Prof. Aixin Sun, who is also the Assistant Chair (Academic).

Dr. Wang have been recognized as the 2022 AI 2000 Most Influential Scholar Honorable Mention in Natural Language Processing.

ORCID: 0000-0002-7709-2543

Interests
  • Pre-trained Language Model
  • Dialog System
  • Sentiment Analysis
Education
  • PhD in Artificial Intelligence, 2019

    Tsinghua University

Projects

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Pre-trained Language Model
Pre-trained Language Models have achieved significant success.
Arabic Language Model (ALM 1.0)
We develop and open Arabic Language Model (ALM).

Recent Publications

(2022). CORT: A New Baseline for Comparative Opinion Classification by Dual Prompts. In Findings of the EMNLP 2022.

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(2022). Packet Representation Learning for Traffic Classification. In KDD 2022.

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(2022). Interactive Information Extraction by Semantic Information Graph. In IJCAI 2022.

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(2022). A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict. In Findings of NAACL 2022.

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(2019). Path Travel Time Estimation using Attribute-related Hybrid Trajectories Network. In CIKM 2019.

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(2019). Aspect-level Sentiment Analysis using AS-Capsules. In WWW 2019.

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(2018). Sentiment Analysis by Capsules. In WWW 2018.

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(2016). Attention-based LSTM for Aspect-level Sentiment Classification. In EMNLP 2016.

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Accomplish­ments

Excellent Ph.D Graduate of the Department of Computer Science, Tsinghua University

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