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Shexia He

Shexia He has 3 papers in our library, in 2018–2021, most of them on Semantic role labeling, Syntax & grammar formalisms, Dependency parsing; often with Hai Zhao, Zuchao Li, Jiaxun Cai.

3 papers in our library · 2018–2021

OpenAlex · h-index 10 · 16 works · 599 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 140 times in our library · ⭐ Paper Stars ranking: #3770

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Shanghai Jiao Tong UniversityShanghai · China2018–2022 · 13 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 works

🧭 Topics 4Research subjects and languages the work is about.Dependency parsing · 1 workSemantic role labeling · 2 worksSyntax & grammar formalisms · 2 worksEnglish · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Semantic role labeling · 1 work

 Works by year

2020s

20211 paperSyntax Role for Neural Semantic Role Labeling

2010s

20182 papersShexia He's papers of 2018

 Papers

The most cited first (OpenAlex and our library).

  1. Syntax for Semantic Role Labeling, To Be, Or Not To Be (2018 · 212 citations)
    Some recent neural semantic role labeling (SRL) systems perform very well without any syntactic input. This raises the question of whether dependency parses still help. He et al. examine this for dependency-based SRL.
  2. Seq2seq Dependency Parsing (2018 · 153 citations)
    Earlier seq2seq dependency parsers did not output trees directly. They generated sequences of transition actions, so a transition algorithm was still needed to build the final structure. Li et al. remove this dependence. Their encoder–decoder model has a BiLSTM encoder and an LSTM decoder with attention. For every…
  3. Syntax Role for Neural Semantic Role Labeling (2021 · 29 citations)
    Early neural SRL systems matched or beat syntax-heavy models without any parse input, so it became unclear whether syntax still matters for semantic role labeling.

 Co-authors here

4 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 140 times (of the 141,840 papers whose bibliographies we read); 17 citing papers with a page here →.

Updated

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