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Tianhao Wu

Tianhao Wu has 2 papers in our library, in 2024–2025, most of them on Language models & pretraining, Evaluation & benchmarks; often with Banghua Zhu, Ion Gabriel Stoica, Jason Weston.

2 papers in our library · 2024–2025

OpenAlex · ORCID · h-index 12 · 50 works · 478 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 258 times in our library · ⭐ Paper Stars ranking: #5144

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

🏛️State Administration for Market RegulationBeijing · China2026 · 1 papercurrent🎓Beijing University of Posts and TelecommunicationsBeijing · China2017–2023 · 13 papers🎓University of California, BerkeleyBerkeley · United States2021–2025 · 4 papers🎓Peking UniversityBeijing · China2021–2023 · 3 papers🎓Beijing Institute of TechnologyBeijing · China2024–2025 · 2 papers🎓Hefei University of TechnologyHefei · China2009 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 20 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 2Research subjects and languages the work is about.Evaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline (2024 · 210 citations)
    Static LLM benchmarks saturate quickly, can leak into training data, and mostly test close-ended tasks. Expert-built sets are expensive: GPQA's 500 questions reportedly cost over $120,000. Live human evaluation such as Chatbot Arena is too slow for developers to use routinely. The authors present BenchBuilder, an…
  2. Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge (2025 · 64 citations)
    Self-Rewarding training lets an LLM improve without human labels by scoring its own outputs. However, it trains only the model's answering skill. Its evaluation skill stays fixed, so gains plateau after a few iterations and the model risks reward hacking. The authors add a third role, a meta-judge, alongside the…

 Co-authors here

11 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 258 times (of the 149,439 papers whose bibliographies we read); 83 citing papers with a page here →.

Updated

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