---
title: "Ning Wang · Jiangnan University — author profile and papers"
description: "Ning Wang, Jiangnan University: 5 papers on Elamur Research (2024–2026), h-index 0 — affiliations, topics, co-authors and who cites them…"
canonical: "https://research.elamur.ai/free/en/authors/ning-wang/"
---
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# Ning Wang

Ning 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/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Kai Wang](https://md.research.elamur.ai/free/en/authors/kai-wang/), [Shiguo Lian](https://md.research.elamur.ai/free/en/authors/shiguo-lian/), [Zhaoxiang Liu](https://md.research.elamur.ai/free/en/authors/zhaoxiang-liu/).

5 papers in our library · 2024–2026

[OpenAlex](https://openalex.org/A5139811044) · [**h-index 0**](https://openalex.org/authors/A5139811044) · [4 works](https://openalex.org/works?filter=author.id:A5139811044) · [0 citations](https://openalex.org/works?filter=author.id:A5139811044&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/ning-wang/#papers) · [🔗 Cited 2 times in our library](https://md.research.elamur.ai/free/en/authors/ning-wang/cited-by/) · [⭐ Paper Stars ranking: #10624](https://md.research.elamur.ai/free/en/paper-stars/page/107/#star-10624)

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=Ning+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ning+Wang) · [dblp](https://dblp.org/search?q=Ning+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Ning+Wang)

## Affiliations

[🏢**China United Network Communications Group** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/china-united-network-communications-group/) · [🎓**Guangzhou University** Guangzhou · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/guangzhou-university/) · [🎓**Jiangnan University** Wuxi · China 2026 · 1 paper*current*](https://ror.org/04mkzax54) · [🎓**University of South Florida** Tampa · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/university-of-south-florida/)

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 8 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 5 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/) · [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 4 Research subjects and languages the work is about.[Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [English · 1 work](https://md.research.elamur.ai/free/en/topics/english/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/)

## Works by year

### 2020s

[**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/ning-wang/year/2026/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/ning-wang/year/2024/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Methodology of Adapting Large English Language Models for Specific Cultural Contexts](https://md.research.elamur.ai/free/en/papers/zhang-2024-methodology-adapting-large-english-language/)** *(2024 · 2 citations)* Leading LLMs are trained mostly on English, so they lack local knowledge and can clash with local values when used in another culture.
2. **[HqeKV: Towards Hybrid Quantization and Eviction for KV Cache in Long-Context LLM Inference](https://md.research.elamur.ai/free/en/papers/wang-2026-hqekv-hybrid-quantization-eviction-kv/)** *(2026 · 1 citation)* Storing key-value (KV) pairs during autoregressive decoding avoids recomputation, but the cache grows with sequence length and can outweigh the model's own memory in long-context serving.
3. **[Test of Time: Rethinking Temporal Signal of Benchmark Contamination](https://md.research.elamur.ai/free/en/papers/zhang-2026-test-time-rethinking-temporal-signal/)** *(2026 · 1 citation)* Researchers often treat a drop in LLM accuracy on questions published after a model's training cutoff as evidence that older questions leaked into its training data.
4. **[Mixture of Heterogeneous Grouped Experts for Language Modeling](https://md.research.elamur.ai/free/en/papers/ma-2026-mixture-heterogeneous-grouped-experts-language/)** *(2026)* Standard Mixture-of-Experts (MoE) language models use experts of one fixed size, so every token receives the same compute regardless of how hard it is to predict.
5. **[Self-Guided Alignment: Adaptive Preference Sensing for Multi-Objective Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-self-guided-alignment-adaptive-preference/)** *(2026)* Prompt-conditioned methods for multi-objective LLM alignment, such as RiC, CPO, and SteerLM, have a mismatch between training and inference.

## Co-authors here

12 of 17 co-authors with a page, the most papers together first.

- [Kai Wang](https://md.research.elamur.ai/free/en/authors/kai-wang/) ×2
- [Shiguo Lian](https://md.research.elamur.ai/free/en/authors/shiguo-lian/) ×2
- [Zhaoxiang Liu](https://md.research.elamur.ai/free/en/authors/zhaoxiang-liu/) ×2
- [Bernhard Schölkopf](https://md.research.elamur.ai/free/en/authors/bernhard-scholkopf/)
- [Ge Yu](https://md.research.elamur.ai/free/en/authors/ge-yu/)
- [He Wang](https://md.research.elamur.ai/free/en/authors/he-wang/)
- [Keenan Samway](https://md.research.elamur.ai/free/en/authors/keenan-samway/)
- [Mrinmaya Sachan](https://md.research.elamur.ai/free/en/authors/mrinmaya-sachan/)
- [Punya Syon Pandey](https://md.research.elamur.ai/free/en/authors/punya-syon-pandey/)
- [Shuming Shi](https://md.research.elamur.ai/free/en/authors/shuming-shi/)
- [Terry Jingchen Zhang](https://md.research.elamur.ai/free/en/authors/terry-jingchen-zhang/)
- [Wenyuan Jiang](https://md.research.elamur.ai/free/en/authors/wenyuan-jiang/)

## 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
- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/)

## Cited by

Papers of our library cite their works 2 times (of the 149,439 papers whose bibliographies we read); [1 citing paper with a page here →](https://md.research.elamur.ai/free/en/authors/ning-wang/cited-by/).

Updated 1 November 2026
