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Jian Guo

Jian Guo has 3 papers in our library, in 2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Evaluation & benchmarks; often with Chengjin Xu, Xuhui Jiang, Cehao Yang.

3 papers in our library · 2026

OpenAlex · h-index 1 · 4 works · 1 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 3 times in our library · ⭐ Paper Stars ranking: #10654

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

🎓The Hong Kong University of Science and Technology (Guangzhou)Guangzhou · China2026 · 1 papercurrent

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 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 1 workEvaluation & benchmarks · 1 workMultilingual & cross-lingual NLP · 1 workVision & language · 1 work

 Works by year

2020s

20263 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Select2Reason: Efficient Instruction-Tuning Data Selection for Long-CoT Reasoning (2026 · 4 citations)
    Long chain-of-thought (long-CoT) reasoning can be instilled in LLMs cheaply by supervised fine-tuning on traces generated by strong reasoning models.
  2. DataArc-SynData-Toolkit: A Unified Closed-Loop Framework for Multi-Path, Multimodal, and Multilingual Data Synthesis (2026)
    Synthetic data can ease data shortages for LLMs in specialised domains and low-resource languages, but current tools tend to be hard for non-experts, rely on inconsistent data formats, and handle extra modalities or languages poorly.
  3. JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation (2026)
    Static benchmarks for LLMs saturate quickly, cover a fixed slice of knowledge, risk contamination, and pose questions whose difficulty may not suit the model under test.

 Co-authors here

11 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 3 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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