--- title: "Yonghua Lin — author profile and papers · Vision & language" description: "Yonghua Lin, Beijing Academy of Artificial Intelligence: 3 papers on Elamur Research (2026), h-index 19 — affiliations, topics, co-authors and…" canonical: "https://research.elamur.ai/free/en/authors/yonghua-lin/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yonghua-lin/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yonghua Lin # Yonghua Lin Yonghua Lin has 3 papers in our library, in 2026, most of them on [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/), [Sentiment & emotion](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/); often with [Hao Zhang](https://md.research.elamur.ai/free/en/authors/hao-zhang/), [Lyu Mengsi](https://md.research.elamur.ai/free/en/authors/lyu-mengsi/), [Yulong Ao](https://md.research.elamur.ai/free/en/authors/yulong-ao/). 3 papers in our library · 2026 [OpenAlex](https://openalex.org/A5103510896) · [**h-index 19**](https://openalex.org/authors/A5103510896) · [54 works](https://openalex.org/works?filter=author.id:A5103510896) · [998 citations](https://openalex.org/works?filter=author.id:A5103510896&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/yonghua-lin/#papers) · [🔗 Cited 14 times in our library](https://md.research.elamur.ai/free/en/authors/yonghua-lin/cited-by/) · [⭐ Paper Stars ranking: #10412](https://md.research.elamur.ai/free/en/paper-stars/page/105/#star-10412) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yonghua+Lin) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yonghua+Lin) · [dblp](https://dblp.org/search?q=Yonghua+Lin) · [ACL Anthology](https://aclanthology.org/search/?q=Yonghua+Lin) ## Affiliations [🔬**Beijing Academy of Artificial Intelligence** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/labs/beijing-academy-of-artificial-intelligence/) · [🔬**Changchun Institute of Applied Chemistry** Changchun · China 1987–2004 · 31 papers](https://ror.org/00h52n341) · [🏛️**Chinese Academy of Sciences** Beijing · China 1996–2004 · 14 papers](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🔬**Academia Sinica** Taipei · Taiwan 1989–1994 · 3 papers](https://md.research.elamur.ai/free/en/labs/academia-sinica/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 8 The field of science this work belongs to (OpenAlex fields).[Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Signal Processing · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/signal-processing/) 🧭 Topics 3 Research subjects and languages the work is about.[Efficient models & compression · 2 works](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Vision & language · 2 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Sentiment & emotion · 1 work](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/yonghua-lin/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations](https://md.research.elamur.ai/free/en/papers/sun-2026-emotiontalk-interactive-chinese-multimodal-emotion/)** *(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. **[PDTrim: Targeted Pruning for Prefill-Decode Disaggregation in Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-pdtrim-targeted-pruning-prefill-decode/)** *(2026 · 6 citations)* Production LLM serving often splits inference into two parts: a prefill stage that processes the prompt and builds the KV cache, and a decode stage that generates tokens. 3. **[TrimTokenator: Towards Adaptive Visual Token Pruning for Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-trimtokenator-adaptive-visual-token-pruning/)** *(2026 · 6 citations)* Large multimodal models turn an image into thousands of visual tokens. Because self-attention cost grows quadratically with sequence length, these tokens make inference slow and memory-hungry. The authors first compare the two modalities through attention patterns, semantic distribution and repeated information. They… ## Co-authors here 11 co-authors with a page, the most papers together first. - [Hao Zhang](https://md.research.elamur.ai/free/en/authors/hao-zhang/) ×2 - [Lyu Mengsi](https://md.research.elamur.ai/free/en/authors/lyu-mengsi/) ×2 - [Yulong Ao](https://md.research.elamur.ai/free/en/authors/yulong-ao/) ×2 - [Haoqin Sun](https://md.research.elamur.ai/free/en/authors/haoqin-sun/) - [Hui Wang](https://md.research.elamur.ai/free/en/authors/hui-wang/) - [Jiaming Zhou](https://md.research.elamur.ai/free/en/authors/jiaming-zhou/) - [Jinghua Zhao](https://md.research.elamur.ai/free/en/authors/jinghua-zhao/) - [Shiwan Zhao](https://md.research.elamur.ai/free/en/authors/shiwan-zhao/) - [Xi Yang](https://md.research.elamur.ai/free/en/authors/xi-yang/) - [Yequan Wang](https://md.research.elamur.ai/free/en/authors/yequan-wang/) - [Zhuo Chen](https://md.research.elamur.ai/free/en/authors/zhuo-chen/) ## 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](https://md.research.elamur.ai/free/en/venues/findings/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×2 - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ## Cited by Papers of our library cite their works 14 times (of the 149,439 papers whose bibliographies we read); [7 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yonghua-lin/cited-by/). Updated 31 October 2026