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Ye Wang

Ye Wang has 4 papers in our library, in 2018–2026, most of them on Language models & pretraining, Sentiment & emotion, Speech & spoken language; often with Guodong Zhou, Han Wang, Hongfu Liu.

4 papers in our library · 2018–2026

OpenAlex · h-index 0 · 4 works · 0 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #10638

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

🎓Fudan UniversityShanghai · China2026 · 1 papercurrent🎓National University of Defense TechnologyChangsha · China2026 · 1 papercurrent🎓Soochow UniversitySuzhou · 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 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 4 worksArts and Humanities · 4 worksComputer Science · 4 worksLanguage and Linguistics · 4 worksExperimental and Cognitive Psychology · 1 workPsychology · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 8Research subjects and languages the work is about.English · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 2 worksSpeech & spoken language · 1 workMultilingual & cross-lingual NLP · 1 workReasoning · 1 workSentiment & emotion · 1 workVision & language · 1 work

 Works by year

2020s

20263 papers

2010s

20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. English Out-of-Vocabulary Lexical Evaluation Task (2018 · 3 citations)
    The paper proposes a benchmark for words a model has never seen: out-of-vocabulary (OOV) items that occur only in test material, so their meaning must come from surrounding text.
  2. Unlocking Large Audio-Language Models for Interactive Language Learning (2026 · 1 citation)
    Traditional Computer-Assisted Pronunciation Training (CAPT) tools mostly return error locations or numeric scores, which L2 learners often struggle to turn into concrete practice.
  3. Exploring Multilingual Pre-trained Language Model for Aspect-based Sentiment Analysis (2026)
    This work targets aspect-based sentiment analysis (ABSA) framed as quadruple prediction (aspect, opinion, category, polarity).
  4. Simple-VGC: Enhancing Visual Grounding in Multimodal Reasoning via Adaptive Tool Composition (2026)
    Multimodal large language models (MLLMs) often lose track of visual evidence while reasoning. The authors identify three distinct grounding failures. Long-Context Grounding Error occurs when the image's influence fades over long outputs. Fine-Grained Grounding Error occurs when low resolution hides details. Regional…

 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.

 Cited by

Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read).

Updated

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