Elamur Research⌕
☰
home / authors / Longhui Yu

Longhui Yu

Longhui Yu has 3 papers in our library, in 2023–2024, most of them on Language models & pretraining, Reasoning; often with Han Shi, James Tin-Yau Kwok, Weisen Jiang.

3 papers in our library · 2023–2024

No OpenAlex profile matched yet.

📄 3 works in our library · 🔗 Cited 623 times in our library · ⭐ Paper Stars ranking: #3671

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

 Fields, topics and concepts

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

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksMathematics · 2 worksComputational Theory and Mathematics · 1 workApplied Mathematics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 2 works

 Works by year

2020s

20242 papers20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models (2023 · 565 citations)
    Open-source LLMs such as LLaMA-2 lag well behind closed models on multi-step maths word problems. Fine-tuning helps, but it depends on having enough varied training questions. MetaMath addresses this by growing the GSM8K and MATH training sets from the question side as well as the answer side, producing a dataset…
  2. Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision (2024 · 51 citations)
    Current alignment methods learn from human demonstrations or human judgments, so a model's skill may be capped at what people can supervise.
  3. Forward-Backward Reasoning in Large Language Models for Mathematical Verification (2024 · 44 citations)
    The paper addresses a limitation of Self-Consistency in chain-of-thought math solving. Self-Consistency picks the answer that most sampled reasoning chains agree on, and its gains level off as more chains are sampled. Many of its errors are still recoverable, because some sampled chain often reaches the right answer…

 Co-authors here

12 of 14 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 623 times (of the 149,439 papers whose bibliographies we read); 245 citing papers with a page here →.

Updated

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