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Qingyu Tan

Qingyu Tan has 4 papers in our library, in 2021–2023, most of them on Language models & pretraining, Information extraction, Efficient models & compression; often with Lidong Bing, Hwee Tou Ng, Liying Cheng.

4 papers in our library · 2021–2023

OpenAlex · h-index 7 · 12 works · 456 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 267 times in our library · ⭐ Paper Stars ranking: #3007

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 · Singapore2020–2024 · 12 paperscurrent🏢Alibaba GroupHangzhou · China2020–2024 · 10 paperscurrent🏢Alibaba DAMO AcademyHangzhou · China2020–2024 · 9 paperscurrent🏢Alibaba GroupGeorge Town · Cayman Islands2020–2024 · 8 paperscurrent🎓Nanyang Technological UniversitySingapore · Singapore2021 · 2 papers🎓Singapore University of Technology and DesignSingapore · Singapore2021 · 2 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 2 worksInformation extraction · 2 worksEfficient models & compression · 1 work

 Works by year

2020s

20231 paperSeaLLMs — Large Language Models for Southeast Asia20222 papersQingyu Tan's papers of 202220211 paperOn the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation

 Papers

The most cited first (OpenAlex and our library).

  1. On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation (2021 · 204 citations)
    Adapter-based tuning inserts small trainable modules into a frozen pretrained language model (PrLM). Earlier work valued it mainly for saving parameters. This paper asks a different question: when does it actually beat full fine-tuning? The authors use the Houlsby et al. adapter design. Each transformer layer gets…
  2. Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation (2022 · 169 citations)
    The paper addresses document-level relation extraction (DocRE), where relations must be identified between every ordered pair of given entities across a whole document.
  3. Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction (2022 · 151 citations)
    DocRED is a standard benchmark for document-level relation extraction. It was built by having annotators filter candidate triples suggested by Wikidata distant supervision and an early RE model. The authors show that this process left many true relations unlabeled, so false negatives are widespread. They trace the…
  4. SeaLLMs — Large Language Models for Southeast Asia (2023 · 92 citations)
    Mainstream LLMs are trained mostly on English. As a result, they handle Southeast Asian languages poorly, especially those written in non-Latin scripts, which standard BPE tokenizers break into very long token sequences. SeaLLMs are open models for Southeast Asian languages, built by adapting English-centric…

 Co-authors here

12 of 17 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 267 times (of the 141,840 papers whose bibliographies we read); 19 citing papers with a page here →.

Updated

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