--- title: "Yitong Wang — author profile and papers — Elamur Research" description: "Yitong Wang: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/yitong-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yitong-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yitong Wang # Yitong Wang Yitong Wang has 2 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Haoyu Wang](https://md.research.elamur.ai/free/en/authors/haoyu-wang/), [Jiansheng Wei](https://md.research.elamur.ai/free/en/authors/jiansheng-wei/), [Junlan Feng](https://md.research.elamur.ai/free/en/authors/junlan-feng/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139757456) · [**h-index 0**](https://openalex.org/authors/A5139757456) · [1 works](https://openalex.org/works?filter=author.id:A5139757456) · [0 citations](https://openalex.org/works?filter=author.id:A5139757456&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yitong-wang/#papers) · [⭐ Paper Stars ranking: #11746](https://md.research.elamur.ai/free/en/paper-stars/page/118/#star-11746) 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=Yitong+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yitong+Wang) · [dblp](https://dblp.org/search?q=Yitong+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Yitong+Wang) ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 6 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) 🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/yitong-wang/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Why Did Apple Fall: Evaluating Curiosity in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-why-did-apple-fall-evaluating/)** *(2026 · 1 citation)* Curiosity-inspired intrinsic rewards are increasingly used in RL training of LLMs, but it has not been checked whether these models actually behave in curious ways, or whether the reported gains simply come from amplified statistical signals such as entropy. 2. **[Soft Orthogonal Low-Rank Adaptation for Knowledge Sharing in Large Language Model Continual Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-soft-orthogonal-low-rank-adaptation/)** *(2026)* The paper addresses continual learning (CL) for large language models. Full retraining is too costly at this scale, and most existing CL methods focus only on preventing catastrophic forgetting, without exploiting knowledge that tasks could share. The authors first observe that better-performing CL models produce… ## Co-authors here 10 co-authors with a page, the most papers together first. - [Haoyu Wang](https://md.research.elamur.ai/free/en/authors/haoyu-wang/) - [Jiansheng Wei](https://md.research.elamur.ai/free/en/authors/jiansheng-wei/) - [Junlan Feng](https://md.research.elamur.ai/free/en/authors/junlan-feng/) - [Lijun Mei](https://md.research.elamur.ai/free/en/authors/lijun-mei/) - [Qian Hu](https://md.research.elamur.ai/free/en/authors/qian-hu/) - [Sihang Jiang](https://md.research.elamur.ai/free/en/authors/sihang-jiang/) - [Xiaojun Meng](https://md.research.elamur.ai/free/en/authors/xiaojun-meng/) - [Xue Han](https://md.research.elamur.ai/free/en/authors/xue-han/) - [Yanghua Xiao](https://md.research.elamur.ai/free/en/authors/yanghua-xiao/) - [Ziqing Wang](https://md.research.elamur.ai/free/en/authors/ziqing-wang/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [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/) - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) Updated 1 November 2026