--- title: "Lei Liang — author profile and papers — Elamur Research" description: "Lei Liang, Ant Group: 4 papers on Elamur Research (2025–2026), h-index 1 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/lei-liang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/lei-liang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Lei Liang # Lei Liang Lei Liang has 4 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Question answering](https://md.research.elamur.ai/free/en/topics/question-answering/), [Knowledge graphs & ontologies](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/); often with [Huajun Chen](https://md.research.elamur.ai/free/en/authors/huajun-chen/), [Wen Zhang](https://md.research.elamur.ai/free/en/authors/wen-zhang/), [Mengshu Sun](https://md.research.elamur.ai/free/en/authors/mengshu-sun/). 4 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5139716188) · [**h-index 1**](https://openalex.org/authors/A5139716188) · [13 works](https://openalex.org/works?filter=author.id:A5139716188) · [1 citations](https://openalex.org/works?filter=author.id:A5139716188&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/lei-liang/#papers) · [🔗 Cited 12 times in our library](https://md.research.elamur.ai/free/en/authors/lei-liang/cited-by/) · [⭐ Paper Stars ranking: #10476](https://md.research.elamur.ai/free/en/paper-stars/page/105/#star-10476) 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=Lei+Liang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Lei+Liang) · [dblp](https://dblp.org/search?q=Lei+Liang) · [ACL Anthology](https://aclanthology.org/search/?q=Lei+Liang) ## Affiliations [🏢**Ant Group** Hangzhou · China 2025–2026 · 14 papers*current*](https://md.research.elamur.ai/free/en/companies/ant-group/) · [🎓**Zhejiang University** Hangzhou · China 2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/universities/zhejiang-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 5 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [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/) · [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/) 🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Knowledge graphs & ontologies · 1 work](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Question answering · 1 work](https://md.research.elamur.ai/free/en/topics/question-answering/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/lei-liang/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/lei-liang/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[RTQA : Recursive Thinking for Complex Temporal Knowledge Graph Question Answering with Large Language Models](https://md.research.elamur.ai/free/en/papers/gong-2025-rtqa-recursive-thinking-complex-temporal/)** *(2025 · 9 citations)* Questions over temporal knowledge graphs (TKGs) often combine several time conditions, such as an implicit anchor event plus an ordering requirement like "last." Existing TKGQA systems, including LLM-based ones, tend to hallucinate on such questions. 2. **[Sparse-RL: Breaking the Memory Wall in LLM Reinforcement Learning via Stable Sparse Rollouts](https://md.research.elamur.ai/free/en/papers/luo-2026-sparse-rl-breaking-memory-wall/)** *(2026 · 4 citations)* Long reasoning rollouts in LLM reinforcement learning store large KV caches. This memory cost limits batch sizes and GPU utilization, especially since rollout generation takes most of the training time. The authors ask whether training-free KV compression, built for inference, can be used during rollouts. They find… 3. **[Temp-R1: A Unified Autonomous Agent for Complex Temporal KGQA via Reverse Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/gong-2026-temp-r1-unified-autonomous-agent/)** *(2026 · 4 citations)* Temp-R1 addresses question answering over temporal knowledge graphs (TKGQA), where facts are timestamped quadruples and questions often combine multi-hop links with time constraints. 4. **[Know the Known and the Unknown: Reasonable Answer Generation with Knowledge-Informed Citations](https://md.research.elamur.ai/free/en/papers/zhang-2026-know-known-unknown-reasonable-answer/)** *(2026)* Citation-augmented question answering helps users verify LLM outputs. Existing benchmarks (ALCE, LongCite, SynSciQA, WebCiteS) have three weaknesses: they cite at the coarse chunk or sentence level, they assume the references always contain the answer, and they rely on plain SFT. The authors present KFC… ## Co-authors here 12 of 18 co-authors with a page, the most papers together first. - [Huajun Chen](https://md.research.elamur.ai/free/en/authors/huajun-chen/) ×3 - [Wen Zhang](https://md.research.elamur.ai/free/en/authors/wen-zhang/) ×3 - [Mengshu Sun](https://md.research.elamur.ai/free/en/authors/mengshu-sun/) ×2 - [Zhaoyan Gong](https://md.research.elamur.ai/free/en/authors/zhaoyan-gong/) ×2 - [Zhiqiang Liu](https://md.research.elamur.ai/free/en/authors/zhiqiang-liu/) ×2 - [Zhizhen Liu](https://md.research.elamur.ai/free/en/authors/zhizhen-liu/) ×2 - [Bohan Zhang](https://md.research.elamur.ai/free/en/authors/bohan-zhang/) - [Jing Zhang](https://md.research.elamur.ai/free/en/authors/jing-zhang/) - [Jun Xu](https://md.research.elamur.ai/free/en/authors/jun-xu/) - [Ke Wang](https://md.research.elamur.ai/free/en/authors/ke-wang/) - [Lingbing Guo](https://md.research.elamur.ai/free/en/authors/lingbing-guo/) - [Sijia Luo](https://md.research.elamur.ai/free/en/authors/sijia-luo/) ## 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 - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/) ## Cited by Papers of our library cite their works 12 times (of the 149,439 papers whose bibliographies we read); [4 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/lei-liang/cited-by/). Updated 2 November 2026