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Michael Tang

Michael Tang has 2 papers in our library, in 2024, most of them on Language models & pretraining, Evaluation & benchmarks, Reasoning; often with Quan Shi, Hongjin Su, Howard Yen.

2 papers in our library · 2024

OpenAlex · ORCID · h-index 9 · 46 works · 431 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 98 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6753

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

🎓University of Technology SarawakSibu2024–2026 · 4 paperscurrent🎓University of Colorado DenverDenver · United States1999–2020 · 14 papers🎓Universiti Sains MalaysiaGeorge Town · Malaysia2020–2024 · 6 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksInformation Systems · 2 worksLanguage and Linguistics · 2 worksComputer Science Applications · 1 work

🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 1 workEvaluation & benchmarks · 1 workInformation retrieval & search · 1 workReasoning · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Inverted index · 1 work

 Works by year

2020s

20242 papers

 Papers

The most cited first (OpenAlex and our library).

  1. BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval (2024 · 77 citations)
    Standard retrieval benchmarks such as BEIR and MTEB mostly test search-engine-style questions. In these, relevant documents share many words or meanings with the query. Many real needs are harder. A programmer may need documentation for a function that is never named in the question, or a student may need a problem…
  2. Can Language Models Solve Olympiad Programming? (2024 · 28 citations)
    Widely used code benchmarks such as HumanEval and MBPP are now nearly saturated, so they no longer show where language models fall short in algorithmic reasoning.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive RetrievalarXiv:2407.12883Hongjin Su, Howard Yen, Mengzhou Xia, et al.2024 · 77 citations
  2. Atlas of Digital Pathology: A Generalized Hierarchical Histological Tissue Type-Annotated Database for Deep Learning ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetMahdi S. Hosseini et al.2019 · 57 citations
  3. Can Language Models Solve Olympiad Programming?arXiv:2404.10952Quan Shi, Michael Tang, Karthik Narasimhan, et al.2024 · 28 citations

 Co-authors here

10 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 98 times (of the 149,439 papers whose bibliographies we read); 27 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/michael-tang/