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Shuailong Liang

Shuailong Liang has 3 papers in our library, in 2018–2020, most of them on Reasoning; often with Yue Zhang, Cunxiang Wang, Jie Yang.

3 papers in our library · 2018–2020

OpenAlex · h-index 14 · 28 works · 808 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 216 times in our library · ⭐ Paper Stars ranking: #3277

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

🏥Lanzhou University Second HospitalLanzhou · China2026 · 2 paperscurrent🎓Central South UniversityChangsha · China2022–2025 · 17 papers🏥Xiangya Hospital Central South UniversityChangsha · China2022–2025 · 12 papers🎓Singapore University of Technology and DesignSingapore · Singapore2018–2021 · 5 papers🏥First Affiliated Hospital Zhejiang UniversityHangzhou · China2023–2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Concepts, shelves and topics

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksComputer Vision and Pattern Recognition · 3 worksLanguage and Linguistics · 3 works

🧭 Topics 1Research subjects and languages the work is about.Reasoning · 1 work

 Works by year

2020s

20201 paperSemEval-2020 Task 4: Commonsense Validation and Explanation

2010s

20191 paperDoes it Make Sense? And Why? A Pilot Study for Sense Making and Explanation20181 paperDesign Challenges and Misconceptions in Neural Sequence Labeling

 Papers

The most cited first (OpenAlex and our library).

  1. Design Challenges and Misconceptions in Neural Sequence Labeling (2018 · 196 citations)
    Published neural sequence labeling results are often hard to reproduce and compare. Studies differ in data splits, preprocessing, handcrafted features, hyperparameters, hardware, and whether they report a single best run or a mean over seeds. Some even reach opposite conclusions, for example on which optimizer works…
  2. Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation (2019 · 174 citations)
    Existing commonsense benchmarks, such as WSC, COPA and SWAG, probe common sense only indirectly through other tasks.
  3. SemEval-2020 Task 4: Commonsense Validation and Explanation (2020 · 157 citations)
    Commonsense understanding is usually tested indirectly, folded into tasks such as QA, coreference or reading comprehension. That makes it hard to tell whether a system can actually judge plausibility and explain what is wrong. ComVE targets this directly with three subtasks:

 Co-authors here

6 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 216 times (of the 141,840 papers whose bibliographies we read); 24 citing papers with a page here →.

Updated

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