Elamur Research⌕
☰
home / authors / Andrew Zhao

Andrew Zhao

Andrew Zhao has 3 papers in our library, in 2025–2026, most of them on Reasoning, Language models & pretraining; often with Gao Ming Huang, Yang Yue, Qingyun Wu.

3 papers in our library · 2025–2026

OpenAlex · h-index 2 · 12 works · 10 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 261 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #5765

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

🎓Tsinghua UniversityBeijing · China2025–2026 · 4 paperscurrent🎓Georgia Institute of TechnologyAtlanta · United States2026 · 1 papercurrent🎓University of California, IrvineIrvine · United States2026 · 1 papercurrent🎓University of PennsylvaniaPhiladelphia · United States2021–2022 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 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).Artificial Intelligence · 3 worksLanguage and Linguistics · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksMathematics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Reasoning · 2 worksLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? (2025 · 216 citations)
    Reinforcement Learning with Verifiable Rewards (RLVR) is widely credited with giving LLMs new reasoning skills in math and code.
  2. Absolute Zero: Reinforced Self-play Reasoning with Zero Data (2025 · 57 citations)
    Current "zero" RLVR methods skip human-written reasoning traces, but they still train on large human-curated sets of questions and answers.
  3. Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers (2026)
    LLM-based prompt optimizers rewrite a system prompt over many rounds, guided by scored feedback on the model's answers.

All works

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

  1. Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paperYang Yue, Zhiqi Chen, Rui Lu, et al.2025 · 216 citations
  2. Absolute Zero: Reinforced Self-play Reasoning with Zero DataConference on Neural Information Processing Systems (NeurIPS)Andrew Zhao, Yiran Wu, Yang Yue, et al.2025 · 57 citations
  3. Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based OptimizersConference of the European Chapter of the Association for Computational Linguistics (EACL)Andrew Zhao, Reshmi Ghosh, Vitor R. Carvalho, et al.2026
  4. Robostral Navigate ↗arXiv (Cornell University) · no summary yetAbdelaziz Bounhar et al.2026
  5. Shieldstral ↗arXiv (Cornell University) · no summary yetAntonia Calvi et al.2026
  6. SPADE: Self-Play in Adaptive Synthetic Executable Environments ↗arXiv (Cornell University) · no summary yetBo Liu et al.2026

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

Updated

↑ back to top

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