--- title: "Zhenghua Wang · Fudan University — author profile and papers" description: "Zhenghua Wang, Fudan University: 5 papers on Elamur Research (2024–2026), h-index 1 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/zhenghua-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhenghua-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhenghua Wang # Zhenghua Wang Zhenghua Wang has 5 papers in our library, in 2024–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Information retrieval & search](https://md.research.elamur.ai/free/en/topics/information-retrieval/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/); often with [Changze Lv](https://md.research.elamur.ai/free/en/authors/changze-lv/), [Xiaoqing Zheng](https://md.research.elamur.ai/free/en/authors/xiaoqing-zheng/), [Xuanjing Huang](https://md.research.elamur.ai/free/en/authors/xuanjing-huang/). 5 papers in our library · 2024–2026 [OpenAlex](https://openalex.org/A5139851083) · [**h-index 1**](https://openalex.org/authors/A5139851083) · [3 works](https://openalex.org/works?filter=author.id:A5139851083) · [2 citations](https://openalex.org/works?filter=author.id:A5139851083&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/zhenghua-wang/#papers) · [🔗 Cited 57 times in our library](https://md.research.elamur.ai/free/en/authors/zhenghua-wang/cited-by/) · [⭐ Paper Stars ranking: #6810](https://md.research.elamur.ai/free/en/paper-stars/page/69/#star-6810) 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=Zhenghua+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhenghua+Wang) · [dblp](https://dblp.org/search?q=Zhenghua+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Zhenghua+Wang) ## Affiliations [🎓**Fudan University** Shanghai · China 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/fudan-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 6 The field of science this work belongs to (OpenAlex fields).[Computer Science · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [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/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 4 Research subjects and languages the work is about.[Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) 💡 Concepts 1 Key ideas and methods explained on our concept pages.[Retrieval-augmented generation · 1 work](https://md.research.elamur.ai/free/en/concepts/retrieval-augmented-generation/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/zhenghua-wang/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/zhenghua-wang/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/zhenghua-wang/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[Searching for Best Practices in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2024-searching-best-practices-retrieval-augmented/)** *(2024 · 150 citations)* Retrieval-augmented generation (RAG) pipelines consist of many stages, and each stage can be built in several ways. 2. **[Revisiting Jailbreaking for Large Language Models: A Representation Engineering Perspective](https://md.research.elamur.ai/free/en/papers/li-2025-revisiting-jailbreaking-large-language-models/)** *(2025 · 17 citations)* The paper asks why LLMs that have been through safety alignment can still be jailbroken. It approaches the question through representation engineering. The authors argue that refusals of harmful requests come from particular activation signatures inside the model, which they call "safety patterns". To find them, they… 3. **[VIB-Probe: Detecting and Mitigating Hallucinations in Vision-Language Models via Variational Information Bottleneck](https://md.research.elamur.ai/free/en/papers/zhang-2026-vib-probe-detecting-mitigating-hallucinations/)** *(2026 · 3 citations)* Vision-Language Models often describe things that are not actually in the image. Most existing detectors look only at output confidence, such as logit entropy, or rely on external verifiers. VIB-Probe looks inside the model instead. During decoding, it collects the raw per-head attention outputs from every… 4. **[Mitigating Hallucinations in VLMs: Enhancing Visual Attention via Head-Wise Perturbation](https://md.research.elamur.ai/free/en/papers/wang-2026-mitigating-hallucinations-vlms-enhancing-visual/)** *(2026)* Vision-language models often hallucinate because they lean on the language priors of their LLM backbone instead of the image. 5. **[Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling](https://md.research.elamur.ai/free/en/papers/wang-2026-mitigating-position-bias-transformers-layer/)** *(2026)* Long-context LLMs that use RoPE tend to concentrate attention on the start and end of the input. As a result, they underuse content in the middle, a problem known as "lost-in-the-middle." Earlier fixes such as Attention Buckets, MoICE and Ms-PoE mix several RoPE bases or scales. However, they need repeated forward… ## Co-authors here 12 of 15 co-authors with a page, the most papers together first. - [Changze Lv](https://md.research.elamur.ai/free/en/authors/changze-lv/) ×5 - [Xiaoqing Zheng](https://md.research.elamur.ai/free/en/authors/xiaoqing-zheng/) ×4 - [Xuanjing Huang](https://md.research.elamur.ai/free/en/authors/xuanjing-huang/) ×4 - [Yixin Wu](https://md.research.elamur.ai/free/en/authors/yixin-wu/) ×4 - [Feiran Zhang](https://md.research.elamur.ai/free/en/authors/feiran-zhang/) ×3 - [Qi Qian](https://md.research.elamur.ai/free/en/authors/qi-qian/) ×3 - [Xiaohua Wang](https://md.research.elamur.ai/free/en/authors/xiaohua-wang/) ×3 - [Muling Wu](https://md.research.elamur.ai/free/en/authors/muling-wu/) ×2 - [Shizheng Li](https://md.research.elamur.ai/free/en/authors/shizheng-li/) ×2 - [Tianlong Li](https://md.research.elamur.ai/free/en/authors/tianlong-li/) ×2 - [Tianyuan Shi](https://md.research.elamur.ai/free/en/authors/tianyuan-shi/) ×2 - [Zhibo Xu](https://md.research.elamur.ai/free/en/authors/zhibo-xu/) ×2 ## 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/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×2 - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/): [COLING 2025](https://md.research.elamur.ai/free/en/venues/coling/2025/) - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2024](https://md.research.elamur.ai/free/en/venues/emnlp/2024/) ## Cited by Papers of our library cite their works 57 times (of the 149,439 papers whose bibliographies we read); [12 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/zhenghua-wang/cited-by/). Updated 1 November 2026