--- title: "Fang Fang — author profile and papers — Elamur Research" description: "Fang Fang: 4 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/fang-fang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/fang-fang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Fang Fang # Fang Fang Fang Fang 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/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/); often with [Yanan Cao](https://md.research.elamur.ai/free/en/authors/yanan-cao/), [Yubing Ren](https://md.research.elamur.ai/free/en/authors/yubing-ren/), [Li Guo](https://md.research.elamur.ai/free/en/authors/li-guo/). 4 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139777599) · [**h-index 0**](https://openalex.org/authors/A5139777599) · [5 works](https://openalex.org/works?filter=author.id:A5139777599) · [0 citations](https://openalex.org/works?filter=author.id:A5139777599&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/fang-fang/#papers) · [⭐ Paper Stars ranking: #13271](https://md.research.elamur.ai/free/en/paper-stars/page/133/#star-13271) 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=Fang+Fang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Fang+Fang) · [dblp](https://dblp.org/search?q=Fang+Fang) · [ACL Anthology](https://aclanthology.org/search/?q=Fang+Fang) ## 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).[Artificial Intelligence · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 3 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/) · [Hardware and Architecture · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) 🧭 Topics 3 Research subjects and languages the work is about.[Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/fang-fang/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Cognitive Analysis Graph-Guided Multi-Turn Safety Enhancement for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-cognitive-analysis-graph-guided-multi/)** *(2026)* Inference-time safety methods for LLMs often fail in multi-turn chats. They judge a question or answer on its own, apply the same defense instructions to every prompt, and ignore earlier turns. As a result, a request that looks harmless alone can become dangerous in context. The authors propose CogGSE, a… 2. **[EA-Agent: A Structured Multi-Step Reasoning Agent for Entity Alignment](https://md.research.elamur.ai/free/en/papers/nan-2026-ea-agent-structured-multi-step/)** *(2026)* Entity alignment (EA) means finding entities in two knowledge graphs that denote the same real-world object. 3. **[Exons-Detect: Identifying and Amplifying Exonic Tokens via Hidden-State Discrepancy for Robust AI-Generated Text Detection](https://md.research.elamur.ai/free/en/papers/zhu-2026-exons-detect-identifying-amplifying-exonic/)** *(2026)* Zero-shot detectors of machine-written text usually average per-token statistics into a single score. This treats every token as equally useful, so the signal weakens on short inputs or after local edits. Exons-Detect is a training-free detector that weights tokens unequally, borrowing the exon/intron analogy from… 4. **[Rethinking LLM Watermark Detection in Black-Box Settings: A Non-Intrusive Third-Party Framework](https://md.research.elamur.ai/free/en/papers/wang-2026-rethinking-llm-watermark-detection-black/)** *(2026)* Most LLM watermarks share a secret key between the embedding step and the detector. Outsiders such as courts, regulators or platform moderators therefore cannot check a watermark on their own. They must either trust the provider's word or obtain the key, and handing over the key makes forging or removing the… ## Co-authors here 7 co-authors with a page, the most papers together first. - [Yanan Cao](https://md.research.elamur.ai/free/en/authors/yanan-cao/) ×4 - [Yubing Ren](https://md.research.elamur.ai/free/en/authors/yubing-ren/) ×3 - [Li Guo](https://md.research.elamur.ai/free/en/authors/li-guo/) ×2 - [Ge Zhang](https://md.research.elamur.ai/free/en/authors/ge-zhang/) - [Shi Wang](https://md.research.elamur.ai/free/en/authors/shi-wang/) - [Xixun Lin](https://md.research.elamur.ai/free/en/authors/xixun-lin/) - [Zheng Fang](https://md.research.elamur.ai/free/en/authors/zheng-fang/) ## 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/) ×2 - [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 Updated 2 November 2026