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Qika Lin

Qika Lin has 2 papers in our library, in 2023, most of them on Language models & pretraining, Evaluation & benchmarks, Reasoning; often with Erik Cambria, Fangzhi Xu, Jiawei Han.

2 papers in our library · 2023

OpenAlex · ORCID · Wikidata · h-index 22 · 98 works · 1,550 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 128 times in our library · ⭐ Paper Stars ranking: #4539

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

🎓National University of SingaporeSingapore · Singapore2023–2026 · 48 paperscurrent🎓Xi'an Jiaotong UniversityXi'an · China2019–2026 · 28 paperscurrent🎓Beijing Institute of TechnologyBeijing · China2018–2020 · 4 papers

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 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workHealth Informatics · 1 workMedicine · 1 work

🧭 Topics 4Research subjects and languages the work is about.Bias, fairness & safety · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20232 papersQika Lin's papers of 2023

 Papers

The most cited first (OpenAlex and our library).

  1. Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond (2023 · 141 citations)
    The paper asks whether current LLMs reason logically or mostly rely on surface patterns and memorized benchmark content.
  2. A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics (2023 · 86 citations)
    This survey asks how large language models are changing healthcare AI and what still prevents their real-world use.

 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 128 times (of the 141,840 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated

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