---
title: "Ziheng Wang — author profile and papers — Elamur Research"
description: "Ziheng Wang, Northwestern Polytechnical University: 5 papers on Elamur Research (2020–2026), h-index 0 — affiliations, topics, co-authors…"
canonical: "https://research.elamur.ai/free/en/authors/ziheng-wang/"
---
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# Ziheng Wang

Ziheng Wang has 5 papers in our library, in 2020–2026, 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/), [GPU & parallel computing](https://md.research.elamur.ai/free/en/topics/gpu-parallel-computing/); often with [Diyi Yang](https://md.research.elamur.ai/free/en/authors/diyi-yang/), [Feng Zhao](https://md.research.elamur.ai/free/en/authors/feng-zhao/), [Hongyu Chen](https://md.research.elamur.ai/free/en/authors/hongyu-chen/).

5 papers in our library · 2020–2026

[OpenAlex](https://openalex.org/A5139799115) · [**h-index 0**](https://openalex.org/authors/A5139799115) · [3 works](https://openalex.org/works?filter=author.id:A5139799115) · [0 citations](https://openalex.org/works?filter=author.id:A5139799115&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/ziheng-wang/#papers) · [🔗 Cited 124 times in our library](https://md.research.elamur.ai/free/en/authors/ziheng-wang/cited-by/) · [⭐ Paper Stars ranking: #5504](https://md.research.elamur.ai/free/en/paper-stars/page/56/#star-5504)

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

## Affiliations

[🎓**Northwestern Polytechnical University** Xi'an · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/northwestern-polytechnical-university/) · [🎓**Renmin University of China** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/renmin-university-of-china/)

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/) · [Computer Vision and Pattern Recognition · 3 works](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 5 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) · [GPU & parallel computing · 1 work](https://md.research.elamur.ai/free/en/topics/gpu-parallel-computing/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/)

## Works by year

### 2020s

[**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/ziheng-wang/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/ziheng-wang/year/2025/) · [**2020** 1 paper](https://md.research.elamur.ai/free/en/authors/ziheng-wang/year/2020/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Structured Pruning of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2020-structured-pruning-large-language-models/)** *(2020 · 202 citations)* Large pretrained language models are expensive to run, and the standard ways of shrinking them each fall short.
2. **[UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision](https://md.research.elamur.ai/free/en/papers/fang-2026-unicorn-self-improving-unified-multimodal/)** *(2026 · 11 citations)* Unified Multimodal Models (UMMs) often judge images accurately but cannot produce scenes of the same quality themselves.
3. **[EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking](https://md.research.elamur.ai/free/en/papers/wei-2025-equibench-benchmarking-large-language-models/)** *(2025 · 8 citations)* EquiBench asks whether large language models actually grasp what code does or mostly react to how it looks.
4. **[Exploring Attention Attractors in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-exploring-attention-attractors-large-language/)** *(2026)* This paper studies "attention attractors," tokens in large language models that receive an unusually large share of attention. Earlier work has explained these tokens in conflicting ways: as summary tokens, as attention sinks, or as key tokens for KV cache compression. The authors examine them from three angles.
5. **[Response-G1: Explicit Scene Graph Modeling for Proactive Streaming Video Understanding](https://md.research.elamur.ai/free/en/papers/ma-2026-response-g1-explicit-scene-graph/)** *(2026)* In streaming video understanding, a Video-LLM sees footage frame by frame. In the proactive setting, it must also decide when it has seen enough to answer a question about events that may happen later. Earlier solutions take one of three routes. Some fine-tune on frame-level silence/response labels, which tend to be…

## Co-authors here

12 of 20 co-authors with a page, the most papers together first.

- [Diyi Yang](https://md.research.elamur.ai/free/en/authors/diyi-yang/)
- [Feng Zhao](https://md.research.elamur.ai/free/en/authors/feng-zhao/)
- [Hongyu Chen](https://md.research.elamur.ai/free/en/authors/hongyu-chen/)
- [Jiannan Cao](https://md.research.elamur.ai/free/en/authors/jiannan-cao/)
- [Jiaqi Tang](https://md.research.elamur.ai/free/en/authors/jiaqi-tang/)
- [Ke Wang](https://md.research.elamur.ai/free/en/authors/ke-wang/)
- [Lin Chen](https://md.research.elamur.ai/free/en/authors/lin-chen/)
- [Qifeng Chen](https://md.research.elamur.ai/free/en/authors/qifeng-chen/)
- [Qin Jin](https://md.research.elamur.ai/free/en/authors/qin-jin/)
- [Ran Li](https://md.research.elamur.ai/free/en/authors/ran-li/)
- [Tao Lei](https://md.research.elamur.ai/free/en/authors/tao-lei/)
- [Wenxuan Wang](https://md.research.elamur.ai/free/en/authors/wenxuan-wang/)

## 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/) ×2: [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/), [EMNLP 2020](https://md.research.elamur.ai/free/en/venues/emnlp/2020/)

## Cited by

Papers of our library cite their works 124 times (of the 149,439 papers whose bibliographies we read); [22 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/ziheng-wang/cited-by/).

Updated 1 November 2026
