--- title: "Ling Feng · Tsinghua University — author profile and papers" description: "Ling Feng, Tsinghua University: 3 papers on Elamur Research (2025–2026), h-index 2 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/ling-feng/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ling-feng/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ling Feng # Ling Feng Ling Feng has 3 papers in our library, in 2025–2026, 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/); often with [Jiajie Zhang](https://md.research.elamur.ai/free/en/authors/jiajie-zhang/), [Juanzi Li](https://md.research.elamur.ai/free/en/authors/juanzi-li/), [Lei Hou](https://md.research.elamur.ai/free/en/authors/lei-hou/). 3 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5037217474) · [ORCID](https://orcid.org/0000-0001-7164-4661) · [**h-index 2**](https://openalex.org/authors/A5037217474) · [13 works](https://openalex.org/works?filter=author.id:A5037217474) · [14 citations](https://openalex.org/works?filter=author.id:A5037217474&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/ling-feng/#papers) · [🔗 Cited 56 times in our library](https://md.research.elamur.ai/free/en/authors/ling-feng/cited-by/) · [⭐ Paper Stars ranking: #8641](https://md.research.elamur.ai/free/en/paper-stars/page/87/#star-8641) 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=Ling+Feng) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ling+Feng) · [dblp](https://dblp.org/search?q=Ling+Feng) · [ACL Anthology](https://aclanthology.org/search/?q=Ling+Feng) ## Affiliations [🎓**Tsinghua University** Beijing · China 2025 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 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 6 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 3 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/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) 🧭 Topics 2 Research subjects and languages the work is about.[Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/ling-feng/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/ling-feng/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[AdaptThink: Reasoning Models Can Learn When to Think](https://md.research.elamur.ai/free/en/papers/zhang-2025-adaptthink-reasoning-models-can-learn/)** *(2025 · 44 citations)* Large reasoning models such as DeepSeek-R1 produce a long chain of thought before answering, even for easy problems. 2. **[LongReward: Improving Long-context Large Language Models with AI Feedback](https://md.research.elamur.ai/free/en/papers/zhang-2025-longreward-improving-long-context-large/)** *(2025 · 21 citations)* Long-context LLMs are usually fine-tuned on question-answer data that other LLMs generate automatically. That data often contains logical slips, invented facts or incomplete answers, and these flaws carry over into the SFT models. Reinforcement learning could correct such behaviour, but there has been no dependable… 3. **[Chaining the Evidence: Robust Reinforcement Learning for Deep Search Agents with Citation-Aware Rubric Rewards](https://md.research.elamur.ai/free/en/papers/zhang-2026-chaining-evidence-robust-reinforcement-learning/)** *(2026)* Deep search agents built on LLMs are usually trained with reinforcement learning using a binary reward: the final answer is either right or wrong. ## Co-authors here 9 co-authors with a page, the most papers together first. - [Jiajie Zhang](https://md.research.elamur.ai/free/en/authors/jiajie-zhang/) ×3 - [Juanzi Li](https://md.research.elamur.ai/free/en/authors/juanzi-li/) ×3 - [Lei Hou](https://md.research.elamur.ai/free/en/authors/lei-hou/) ×3 - [Xin Lv](https://md.research.elamur.ai/free/en/authors/xin-lv/) ×2 - [Shulin Cao](https://md.research.elamur.ai/free/en/authors/shulin-cao/) - [Yilin Niu](https://md.research.elamur.ai/free/en/authors/yilin-niu/) - [Yuxiao Dong](https://md.research.elamur.ai/free/en/authors/yuxiao-dong/) - [Zhenyu Hou](https://md.research.elamur.ai/free/en/authors/zhenyu-hou/) - [Zhongni Hou](https://md.research.elamur.ai/free/en/authors/zhongni-hou/) ## 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/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/), [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) - [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 56 times (of the 149,439 papers whose bibliographies we read); [26 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/ling-feng/cited-by/). Updated 2 November 2026