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Dongjie Wang

Dongjie Wang has 3 papers in our library, in 2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Evaluation & benchmarks; often with Fengran Mo, Jinghan Zhang, Kunpeng Liu.

3 papers in our library · 2026

OpenAlex · h-index 1 · 6 works · 2 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #10825

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

🎓University of KansasLawrence ·

United States2026 · 5 paperscurrent

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 9Computer Science · 3 works Arts and Humanities · 2 works Artificial Intelligence · 3 works Language and Linguistics · 2 works Computer Vision and Pattern Recognition · 1 work Health Informatics · 1 work Health Information Management · 1 work Health Professions · 1 work Medicine · 1 work

🧭 Topics 4Language models & pretraining · 1 work Reasoning · 1 work Evaluation & benchmarks · 1 work Multilingual & cross-lingual NLP · 1 work

Works by year

2020s

20263 papers

Papers

The most cited first (OpenAlex and our library).

Blind Spot Navigation in Large Language Model Reasoning with Thought Space Explorer (2026 · 3 citations)
Tree-like and multi-chain prompting methods such as ToT usually refine or extend reasoning paths the model has already produced.
ManCC: A Task-Anchored Benchmark for Manchu–Classical Chinese Cross-Lingual Modeling (2026)
Manchu, the official language of the Qing dynasty, is now critically endangered. Translation between Manchu and Classical Chinese has had no shared benchmark, so earlier small studies cannot be compared fairly. The authors build ManCC, which uses bidirectional Manchu–Classical Chinese translation as an anchor task…
RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models (2026)
When LLMs are applied to structured electronic health records, two weaknesses appear. Converting visit sequences into flat text blurs the timing between visits and the identity of individual codes. Each patient is also handled on its own, so the model gains nothing from patterns that recur across the cohort.

Co-authors here

8 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.

Findings of the Association for Computational Linguistics ×3: Findings of the Association for Computational Linguistics 2026 ×3

Cited by

Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated 1 November 2026

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