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Xi Yang

Xi Yang has 2 papers in our library, in 2026, most of them on Vision & language, Sentiment & emotion; often with Haoqin Sun, Hui Wang, Jiaming Zhou.

2 papers in our library · 2026

OpenAlex · h-index 0 · 3 works · 0 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 4 times in our library · ⭐ Paper Stars ranking: #10316

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

🎓Hong Kong University of Science and TechnologyHong Kong · China2026 · 1 papercurrent🎓Jilin UniversityChangchun · 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 8The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksPsychology · 1 workExperimental and Cognitive Psychology · 1 workSignal Processing · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Vision & language · 2 worksSentiment & emotion · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations (2026 · 6 citations)
    Chinese multimodal emotion recognition (MER) has far fewer resources than English. Existing Chinese corpora are mostly clipped from films and TV, so their quality is often low. They also tend to lack conversational structure or rich labels. Emotion captioning additionally relies on unreleased data, which makes…
  2. Specializing Large Models for Oracle Bone Script Interpretation via Component-Grounded Multimodal Knowledge Augmentation (2026 · 1 citation)
    Most AI work on Oracle Bone Script (OBS) treats decipherment as closed-set image classification. That approach cannot handle rare or unseen glyphs, and general Vision-Language Models (VLMs) tend to hallucinate in this low-resource domain. The authors instead treat interpretation as reasoning over a character's parts.…

 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 4 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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