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Ruoxi Ning

Ruoxi Ning has 3 papers in our library, in 2023–2026, most of them on Language models & pretraining, Question answering, Evaluation & benchmarks; often with Yue Zhang, Cheng Deng, Cunxiang Wang.

3 papers in our library · 2023–2026

OpenAlex · h-index 3 · 12 works · 115 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 166 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5315

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 WaterlooWaterloo · Canada2024–2026 · 7 paperscurrent🔬Vector InstituteToronto · Canada2025–2026 · 3 paperscurrent🎓Westlake UniversityHangzhou · China2022–2025 · 3 papers🎓Zhejiang UniversityHangzhou · China2022–2023 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution 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 · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 4Research subjects and languages the work is about.Question answering · 1 workLanguage models & pretraining · 2 worksEvaluation & benchmarks · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4 (2023 · 217 citations)
    Are ChatGPT and GPT-4 really strong at logic-heavy language tasks? The authors test both models on two task families.
  2. NovelQA: Benchmarking Question Answering on Documents Exceeding 200K Tokens (2024 · 29 citations)
    Current LLMs accept context windows of 200K+ tokens, but long-context benchmarks typically average around 60K tokens.
  3. On the Effect of Hyperparameters in Language Modeling for Computational Linguistics (2026)
    Computational linguists often train language models from scratch to test linguistic hypotheses, but they usually rely on a single, loosely chosen configuration.

All works

4 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. Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4arXiv:2304.03439Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, et al.2023 · 217 citations
  2. NovelQA: Benchmarking Question Answering on Documents Exceeding 200K TokensarXiv:2403.12766Cunxiang Wang, Ruoxi Ning, Boqi Pan, et al.2024 · 29 citations
  3. Logical Reasoning in Large Language Models: A Survey ↗arXiv:2502.09100 · no summary yetHanmeng Liu et al.2025 · 25 citations
  4. On the Effect of Hyperparameters in Language Modeling for Computational LinguisticsAnnual Meeting of the Association for Computational Linguistics (ACL)Ruoxi Ning, Yongpeng Zhu, Qingcheng Zeng, et al.2026

 Co-authors here

12 of 15 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 166 times (of the 149,439 papers whose bibliographies we read); 42 citing papers with a page here →.

Updated

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