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Yongcheng Jing

Yongcheng Jing has 3 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning, Efficient models & compression; often with Dacheng Tao, Yingjie Wang, Haifeng Sun.

3 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 17 · 39 works · 1,798 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 14 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9438

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

🎓Nanyang Technological UniversitySingapore · Singapore2025–2026 · 2 paperscurrent🎓Zhejiang UniversityHangzhou · China2017–2021 · 10 papers🎓The University of SydneySydney · Australia2021–2025 · 9 papers🏢Alibaba GroupHangzhou · China2017–2018 · 2 papers🎓South China University of TechnologyGuangzhou · China2015–2016 · 2 papers

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 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 works

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 3 worksReasoning · 1 workEfficient models & compression · 1 work

 Works by year

2020s

20262 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Dynamic Parallel Tree Search for Efficient LLM Reasoning (2025 · 13 citations)
    Tree-of-Thoughts (ToT) style search, often driven by MCTS, improves LLM reasoning, but prior work has focused on accuracy rather than cost.
  2. Distillation Traps and Guards: A Calibration Knob for LLM Distillability (2026 · 1 citation)
    Knowledge distillation (KD) from large LLMs into smaller students sometimes fails without warning, and the same mechanism lets others copy proprietary models.
  3. Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language Models (2026 · 1 citation)
    The paper tackles a weakness in LLM machine unlearning: current techniques tend to suppress only the literal wording of the data to be forgotten.

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. Dynamic Instance Normalization for Arbitrary Style Transfer ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetYongcheng Jing et al.2020 · 192 citations
  2. Dynamic Parallel Tree Search for Efficient LLM ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Yifu Ding, Wentao Jiang, Shunyu Liu, et al.2025 · 13 citations
  3. Distillation Traps and Guards: A Calibration Knob for LLM DistillabilityAnnual Meeting of the Association for Computational Linguistics (ACL)Weixiao Zhan, Yongcheng Jing, Leszek Rutkowski, et al.2026 · 1 citation
  4. Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Huazheng Wang, Yongcheng Jing, Haifeng Sun, et al.2026 · 1 citation

 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 14 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

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