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Jian Wu

Jian Wu has 2 papers in our library, in 2018–2025, most of them on Speech act theory, Machine translation, Dialogue systems; often with Hongwei Wang, Philip S. Yu, Yan Zhang.

2 papers in our library · 2018–2025

OpenAlex · ORCID · h-index 26 · 202 works · 5,233 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 23 citations in our library · ⭐ Paper Star rank #5490

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

🎓Old Dominion UniversityNorfolk · United States2006–2026 · 78 paperscurrent🏛️Chinese Academy of SciencesBeijing · China2017–2026 · 2 paperscurrent🎓University of Science and Technology of ChinaHefei · China2023–2026 · 2 paperscurrent🔬Purple Mountain ObservatoryNanjing · China2026 · 1 papercurrent🎓Pennsylvania State UniversityState College · United States2012–2019 · 22 papers🎓Beihang UniversityBeijing · China2012–2025 · 20 papers🔬State Key Laboratory of Virtual Reality Technology and SystemsBeijing2019–2025 · 14 papers🎓University of VictoriaVictoria · Canada2011–2019 · 9 papers🎓Wuhan University of TechnologyWuhan · China2013–2020 · 6 papers🎓Zhejiang UniversityHangzhou · China2023–2025 · 5 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 29 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 4 Artificial Intelligence · 2 works Arts and Humanities · 2 works Computer Science · 2 works Language and Linguistics · 2 works

🧭 Topics 4 Evaluation & benchmarks · 1 work Machine translation · 1 work Dialogue systems · 1 work Speech act theory · 1 work

 Works by year

2020s

20251 paper

2010s

20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. M-MAD: Multidimensional Multi-Agent Debate for Advanced Machine Translation Evaluation (2025 · 24 citations)
    Using LLMs as judges for machine translation (MT) quality has so far trailed trained metrics such as MetricX and XCOMET. The gap is largest at the segment level, and part of the cause is that existing prompting methods put the whole MQM error taxonomy into one prompt and evaluate in a single pass.
  2. Improved Dynamic Memory Network for Dialogue Act Classification with Adversarial Training (2018 · 14 citations)
    The paper addresses dialogue act (DA) classification: assigning each utterance in a conversation a label such as Question, Answer, Greeting or Backchannel that captures what the speaker intends.

 Co-authors here

5 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 23 times (of the 141,840 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated

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