--- title: "Kaiyu Huang — author profile and papers — Elamur Research" description: "Kaiyu Huang, Beijing Jiaotong University: 5 papers on Elamur Research (2026), h-index 1 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/kaiyu-huang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/kaiyu-huang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Kaiyu Huang # Kaiyu Huang Kaiyu Huang has 5 papers in our library, in 2026, most of them on [Multilingual & cross-lingual NLP](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Low-resource languages](https://md.research.elamur.ai/free/en/topics/low-resource-languages/); often with [Xu Jinan](https://md.research.elamur.ai/free/en/authors/xu-jinan/), [Degen Huang](https://md.research.elamur.ai/free/en/authors/degen-huang/), [Fengran Mo](https://md.research.elamur.ai/free/en/authors/fengran-mo/). 5 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139775113) · [**h-index 1**](https://openalex.org/authors/A5139775113) · [8 works](https://openalex.org/works?filter=author.id:A5139775113) · [13 citations](https://openalex.org/works?filter=author.id:A5139775113&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/kaiyu-huang/#papers) · [🔗 Cited 17 times in our library](https://md.research.elamur.ai/free/en/authors/kaiyu-huang/cited-by/) · [⭐ Paper Stars ranking: #10471](https://md.research.elamur.ai/free/en/paper-stars/page/105/#star-10471) 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=Kaiyu+Huang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Kaiyu+Huang) · [dblp](https://dblp.org/search?q=Kaiyu+Huang) · [ACL Anthology](https://aclanthology.org/search/?q=Kaiyu+Huang) ## Affiliations [🎓**Beijing Jiaotong University** Beijing · China 2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/universities/beijing-jiaotong-university/) 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 8 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) 🧭 Topics 8 Research subjects and languages the work is about.[Multilingual & cross-lingual NLP · 2 works](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Low-resource languages · 1 work](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) ## Works by year ### 2020s [**2026** 5 papers](https://md.research.elamur.ai/free/en/authors/kaiyu-huang/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Think Natively: Unlocking Multilingual Reasoning with Consistency-Enhanced Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhang-2026-think-natively-unlocking-multilingual-reasoning/)** *(2026 · 11 citations)* Reasoning-oriented LLMs that think before answering often handle non-English prompts poorly. They tend to drift into English or a mix of languages during reasoning, and their accuracy drops compared with English. The authors introduce M-Thinker, a family of models (1.5B, 4B, 7B) trained with GRPO using two new reward… 2. **[Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/qi-2026-language-coupled-reinforcement-learning-multilingual/)** *(2026 · 5 citations)* The paper addresses two problems in multilingual retrieval-augmented generation (MRAG). The first is knowledge bias: an LLM answers the same question differently depending on its language. The second is knowledge conflict: passages retrieved from collections in many languages contradict each other. The authors… 3. **[When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life](https://md.research.elamur.ai/free/en/papers/lou-2026-when-helpers-become-hazards-benchmark/)** *(2026 · 1 citation)* Multimodal LLMs are increasingly used as everyday assistants. Their answers can steer people into risky actions even when the user has no harmful intent. Most existing safety benchmarks target jailbreaks or explicit harm, and implicit-risk sets tend to be small or artificial. The authors introduce SaLAD, a benchmark… 4. **[One Pair Suffices: Unlocking Universal Zero-Shot Translation via Cross-Architecture Alignment](https://md.research.elamur.ai/free/en/papers/zong-2026-one-pair-suffices-unlocking-universal/)** *(2026)* Large language models translate fluently but perform poorly on low-resource languages. Specialized multilingual encoders such as NLLB cover many languages but cannot generate as flexibly. The authors argue that the obstacle is aligning the two representation spaces, not a shortage of training data. They propose… 5. **[SiLP: Enhancing Non-Dominant Language Capabilities with a Selective Bidirectional Language Projection Framework](https://md.research.elamur.ai/free/en/papers/liu-2026-silp-enhancing-non-dominant-language/)** *(2026)* Large language models handle English and other dominant languages much better than under-represented ones because their pretraining data is skewed. ## Co-authors here 12 of 20 co-authors with a page, the most papers together first. - [Xu Jinan](https://md.research.elamur.ai/free/en/authors/xu-jinan/) ×3 - [Degen Huang](https://md.research.elamur.ai/free/en/authors/degen-huang/) ×2 - [Fengran Mo](https://md.research.elamur.ai/free/en/authors/fengran-mo/) ×2 - [Xue Zhang](https://md.research.elamur.ai/free/en/authors/xue-zhang/) ×2 - [Yufeng Chen](https://md.research.elamur.ai/free/en/authors/yufeng-chen/) ×2 - [Bo Jin](https://md.research.elamur.ai/free/en/authors/bo-jin/) - [Fandong Meng](https://md.research.elamur.ai/free/en/authors/fandong-meng/) - [Hongliang Li](https://md.research.elamur.ai/free/en/authors/hongliang-li/) - [Huan Liu](https://md.research.elamur.ai/free/en/authors/huan-liu/) - [Hui Xiong](https://md.research.elamur.ai/free/en/authors/hui-xiong/) - [Jian-Yun Nie](https://md.research.elamur.ai/free/en/authors/jian-yun-nie/) - [Jie Zhou](https://md.research.elamur.ai/free/en/authors/jie-zhou/) ## 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/) ×3: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×3 - [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 ## Cited by Papers of our library cite their works 17 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/kaiyu-huang/cited-by/). Updated 2 November 2026