--- title: "Haoran Luo — author profile and papers — Elamur Research" description: "Haoran Luo, Nanyang Technological University: 4 papers on Elamur Research (2026), h-index 1 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/haoran-luo/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/haoran-luo/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Haoran Luo # Haoran Luo Haoran Luo has 4 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Erik Cambria](https://md.research.elamur.ai/free/en/authors/erik-cambria/), [Jiapu Wang](https://md.research.elamur.ai/free/en/authors/jiapu-wang/), [Rui Mao](https://md.research.elamur.ai/free/en/authors/rui-mao/). 4 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139807805) · [**h-index 1**](https://openalex.org/authors/A5139807805) · [5 works](https://openalex.org/works?filter=author.id:A5139807805) · [1 citations](https://openalex.org/works?filter=author.id:A5139807805&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/haoran-luo/#papers) · [🔗 Cited 20 times in our library](https://md.research.elamur.ai/free/en/authors/haoran-luo/cited-by/) · [2 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #8975](https://md.research.elamur.ai/free/en/paper-stars/page/90/#star-8975) 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=Haoran+Luo) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Haoran+Luo) · [dblp](https://dblp.org/search?q=Haoran+Luo) · [ACL Anthology](https://aclanthology.org/search/?q=Haoran+Luo) ## Affiliations [🎓**Nanyang Technological University** Singapore · Singapore 2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/universities/nanyang-technological-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 7 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Political Science and International Relations · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/political-science-and-international-relations/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) 🧭 Topics 4 Research subjects and languages the work is about.[Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Legal AI · 1 work](https://md.research.elamur.ai/free/en/topics/legal-ai/) 💡 Concepts 1 Key ideas and methods explained on our concept pages.[Artificial intelligence · 1 work](https://md.research.elamur.ai/free/en/concepts/artificial-intelligence/) ## Works by year ### 2020s [**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/haoran-luo/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[MUR: Momentum Uncertainty guided Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-mur-momentum-uncertainty-guided-reasoning/)** *(2026 · 8 citations)* Test-time scaling (TTS) makes LLMs reason better but tends to cause overthinking: extra compute goes to every reasoning step, including trivial ones. 2. **[TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-templaterl-structured-template-guided-reinforcement/)** *(2026 · 8 citations)* RL methods such as GRPO strengthen LLM reasoning, but they learn only from rollouts the model samples freely from its own distribution. 3. **[Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-prompt-r1-collaborative-automatic-prompting/)** *(2026 · 3 citations)* Many people struggle to write good prompts for hard problems, which keeps large language models from performing at their best. 4. **[LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence](https://md.research.elamur.ai/free/en/papers/liu-2026-lexgenius-expert-level-benchmark-large/)** *(2026 · 2 citations)* Current legal benchmarks for LLMs mostly score final answers on technical tasks. They tend to ignore "soft" legal skills such as ethical judgment and assessing social impact, and their static public data may have leaked into training sets. LexGenius is a Chinese expert-level benchmark designed to probe legal general… ## All works 6 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them. 1. **[MUR: Momentum Uncertainty guided Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-mur-momentum-uncertainty-guided-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hang Yan, Fangzhi Xu, Rongman Xu, et al.*2026 · 8 citations* 2. **[TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-templaterl-structured-template-guided-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Chonghua Liao, Mingkuan Feng, et al.*2026 · 8 citations* 3. **[Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-prompt-r1-collaborative-automatic-prompting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenjin Liu, Haoran Luo, Xueyuan Lin, et al.*2026 · 3 citations* 4. **[LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence](https://md.research.elamur.ai/free/en/papers/liu-2026-lexgenius-expert-level-benchmark-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenjin Liu, Haoran Luo, Xin Feng, et al.*2026 · 2 citations* 5. **[Beyond Examples: Towards Automated Thought-level In-Context Reasoning for Large Language Models ↗](https://aclanthology.org/2026.acl-long.135/) Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Jinyang Wu et al.*2026* 6. **[MAXS: Meta-Adaptive Exploration with LLM Agents ↗](https://aclanthology.org/2026.findings-acl.670/) Findings of the Association for Computational Linguistics: ACL 2026 · no summary yet**Jian Zhang et al.*2026* ## Co-authors here 12 of 22 co-authors with a page, the most papers together first. - [Erik Cambria](https://md.research.elamur.ai/free/en/authors/erik-cambria/) ×2 - [Jiapu Wang](https://md.research.elamur.ai/free/en/authors/jiapu-wang/) ×2 - [Rui Mao](https://md.research.elamur.ai/free/en/authors/rui-mao/) ×2 - [Wenjin Liu](https://md.research.elamur.ai/free/en/authors/wenjin-liu/) ×2 - [Anh Tuan Luu](https://md.research.elamur.ai/free/en/authors/anh-tuan-luu/) - [Chonghua Liao](https://md.research.elamur.ai/free/en/authors/chonghua-liao/) - [Fangzhi Xu](https://md.research.elamur.ai/free/en/authors/fangzhi-xu/) - [Haiteng Zhao](https://md.research.elamur.ai/free/en/authors/haiteng-zhao/) - [Hang Yan](https://md.research.elamur.ai/free/en/authors/hang-yan/) - [Jian Zhang](https://md.research.elamur.ai/free/en/authors/jian-zhang/) - [Jianhua Tao](https://md.research.elamur.ai/free/en/authors/jianhua-tao/) - [Jinyang Wu](https://md.research.elamur.ai/free/en/authors/jinyang-wu/) ## 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/) ×3: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×3 - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - Findings of the Association for Computational Linguistics: ACL 2026 ## Cited by Papers of our library cite their works 20 times (of the 149,439 papers whose bibliographies we read); [9 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/haoran-luo/cited-by/). Updated 31 October 2026