Elamur Research⌕
☰
home / authors / Jingyuan Huang

Jingyuan Huang

Jingyuan Huang has 4 papers in our library, in 2024–2026, most of them on Language models & pretraining, Dialogue systems, Grammatical error correction & learner language; often with Fan Yang, Haiyan Zhao, Jen-tse Huang.

4 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 6 · 19 works · 139 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 103 times in our library · ⭐ Paper Stars ranking: #7366

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

🎓Zhejiang UniversityHangzhou · China2022–2026 · 5 paperscurrent🎓Rutgers, The State University of New JerseyNew Brunswick · United States2024–2025 · 2 papers🎓Chinese University of Hong KongHong Kong · China2023 · 2 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 8The field of science this work belongs to (OpenAlex fields).Computer Science · 4 worksArts and Humanities · 3 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 workInformation Systems · 1 workSafety Research · 1 workSocial Sciences · 1 work

🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 2 worksDialogue systems · 1 workEnglish · 1 workGrammatical error correction & learner language · 1 work

 Works by year

2020s

20262 papers20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models (2024 · 96 citations)
    The paper examines whether large language models, trained mostly on English text, push English-speaking (largely American) culture onto users who ask questions in other languages.
  2. Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers? (2025 · 36 citations)
    The paper asks where inside a large language model knowledge of different difficulty becomes linearly readable.
  3. H-Mem: Hybrid Multi-Dimensional Memory Management for Long-Context Conversational Agents (2026 · 1 citation)
    Conversational agents that run over long, multi-session dialogues need memory they can query reliably. Most existing memory systems index information along one axis only, usually semantic similarity and occasionally recency, so retrieval often misses evidence that depends on both when and what . H-Mem addresses this…
  4. BRIDGE the Gap: Mitigating Bias Amplification in Automated Scoring of English Language Learners via Inter-group Data Augmentation (2026)
    Automated scorers for student answers, built on deep models and LLMs, can widen score gaps between student groups beyond the gaps in the human labels they learn from.

 Co-authors here

12 of 23 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 103 times (of the 149,439 papers whose bibliographies we read); 39 citing papers with a page here →.

Updated

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