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Hoang D. Nguyen

Hoang D. Nguyen has 4 papers in our library, in 2024–2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Evaluation & benchmarks; often with Barry O'Sullivan, Khanh-Tung Tran.

4 papers in our library · 2024–2026

OpenAlex · ORCID · Wikidata · h-index 20 · 80 works · 1,277 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 82 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #9426

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

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 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.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. UCCIX: Irish-eXcellence Large Language Model (2024 · 14 citations)
    Irish is a UNESCO "definitely endangered" language with only a few hundred million tokens of available text, far below what scaling laws suggest for training an LLM.
  2. Disentangling Continued Pre-Training: Attention-Driven Routing and Semantic Hub Preservation in Language Adaptation (2026 · 1 citation)
    The paper examines what happens inside an LLM during Continued Pre-Training (CPT), the process that teaches it a second language. The authors trace the full training trajectory instead of only the final checkpoint. They use English as the base language and three targets: Irish, Basque, and Chinese. The models are:
  3. LaCoMSA: Language-Consistency Multilingual Self-Alignment with Latent Representation Rewarding (2026)
    Multilingual LLMs tend to answer worse in lower-resource languages than in English. They also often switch into English even when prompted in another language. Earlier preference-optimization fixes such as MAPO, LIDR and ICR depend on outside supervision, such as translation systems or English-trained reward models.
  4. Questionnaire Meets LLM: A Benchmark and Empirical Study of Structural Skills for Understanding Questions and Responses (2026)
    Survey data is a grid of respondents by questions. It is hard for LLMs because cells mix types such as Likert scores, coded multiple-choice options and free text, and answer codes must be decoded through schema metadata. Practitioners also have no evidence on how to turn such data into text for a model. The authors…

All works

6 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. Multi-Agent Collaboration Mechanisms: A Survey of LLMs ↗arXiv:2501.06322 · no summary yetKhanh-Tung Tran et al.2025 · 95 citations
  2. Modular Graph Transformer Networks for Multi-Label Image Classification ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetHoang D. Nguyen, Xuan-Son Vu, Duc-Trong Le2021 · 77 citations
  3. UCCIX: Irish-eXcellence Large Language ModelFrontiers in artificial intelligence and applicationsKhanh-Tung Tran, Barry O'Sullivan, Hoang D. Nguyen2024 · 14 citations

 Co-authors here

2 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 82 times (of the 149,439 papers whose bibliographies we read); 21 citing papers with a page here →.

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