---
title: "Weixun Wang — author profile and papers — Elamur Research"
description: "Weixun Wang, Merck & Co., Inc., Rahway, NJ, USA: 5 papers on Elamur Research (2024–2026), h-index 22 — affiliations, topics, co-authors…"
canonical: "https://research.elamur.ai/free/en/authors/weixun-wang/"
---
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# Weixun Wang

Weixun 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/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Jiaheng Liu](https://md.research.elamur.ai/free/en/authors/jiaheng-liu/), [Shilong Li](https://md.research.elamur.ai/free/en/authors/shilong-li/), [Wenbo Su](https://md.research.elamur.ai/free/en/authors/wenbo-su/).

5 papers in our library · 2024–2026

[OpenAlex](https://openalex.org/A5082417441) · [ORCID](https://orcid.org/0000-0002-2727-8948) · [**h-index 22**](https://openalex.org/authors/A5082417441) · [101 works](https://openalex.org/works?filter=author.id:A5082417441) · [2,737 citations](https://openalex.org/works?filter=author.id:A5082417441&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/weixun-wang/#papers) · [🔗 Cited 246 times in our library](https://md.research.elamur.ai/free/en/authors/weixun-wang/cited-by/) · [5 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #5637](https://md.research.elamur.ai/free/en/paper-stars/page/57/#star-5637)

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

## Affiliations

[🏢**Merck & Co., Inc., Rahway, NJ, USA** Rahway · United States 2012–2026 · 15 papers*current*](https://ror.org/02891sr49) · [🏢**Alibaba Group** Hangzhou · China 2025–2026 · 8 papers*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group/) · [🎓**Chongqing University of Arts and Sciences** Chongqing · China 2018–2026 · 2 papers*current*](https://ror.org/01rcvq140) · [🏢**Alibaba Group** San Mateo · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group-united-states/) · [🎓**University of Florida** Gainesville · United States 2009–2012 · 22 papers](https://md.research.elamur.ai/free/en/universities/university-of-florida/) · [🎓**Tianjin University** Tianjin · China 2019–2023 · 21 papers](https://md.research.elamur.ai/free/en/universities/tianjin-university/) · [🎓**Princeton University** Princeton · United States 1999–2002 · 4 papers](https://md.research.elamur.ai/free/en/universities/princeton-university/) · [🏢**NetEase** Beijing · China 2022–2024 · 3 papers](https://ror.org/00fp6fj05) · [🏢**Jinchuan** Jinchang · China 2007 · 2 papers](https://ror.org/00sxp6h30)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution 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).[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/) · [Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 4 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 5 Research subjects and languages the work is about.[Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/weixun-wang/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/weixun-wang/year/2025/) · [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/weixun-wang/year/2024/)

## Papers

The most cited first (OpenAlex and our library).

1. **[OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework](https://md.research.elamur.ai/free/en/papers/hu-2024-openrlhf-easy-use-scalable/)** *(2024 · 140 citations)* Training LLMs with RLHF and RLVR, especially with PPO, is dominated by text generation. The authors say this phase can take more than 90% of runtime when models produce long chain-of-thought outputs. Existing tools also force a trade-off. TRL, DeepSpeed-Chat and ColossalChat are approachable but weak at inference…
2. **[Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2024-chinese-simpleqa-chinese-factuality/)** *(2024 · 34 citations)* Hallucination remains a major weakness of large language models. Factuality is hard to measure when models produce long answers that mix many claims. OpenAI's SimpleQA addressed this with short fact-seeking questions, but it covers only English. Chinese SimpleQA is a Chinese counterpart: 3,000 short questions, each…
3. **[Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/)** *(2025 · 30 citations)* Reasoning models in the o1 style produce very long chains of thought (CoT). Until this paper, there was no systematic way to check how good those chains are, or whether other models can find the mistakes in them. The authors built DeltaBench to address both gaps. It contains 1,236 problems from Math, Programming, PCB…
4. **[ShopSimulator: Evaluating and Exploring RL-Driven LLM Agent for Shopping Assistants](https://md.research.elamur.ai/free/en/papers/wang-2026-shopsimulator-evaluating-exploring-rl-driven/)** *(2026 · 1 citation)* LLM-based shopping assistants must clarify vague requests through dialogue, use a shopper's profile and history, and pick the right item among near-identical products.
5. **[USB: A COMPREHENSIVE AND UNIFIED SAFETY EVALUATION BENCHMARK FOR MULTIMODAL LARGE LANGUAGE MODELS](https://md.research.elamur.ai/free/en/papers/zheng-2026-usb-comprehensive-unified-safety-evaluation/)** *(2026 · 1 citation)* Existing safety benchmarks for multimodal large language models (MLLMs) cover few risk types and contain few samples.

## All works

10 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

1. **[Multi-Agent Game Abstraction via Graph Attention Neural Network ↗](https://doi.org/10.1609/aaai.v34i05.6211) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Yong Liu et al.*2020 · 247 citations*
2. [**OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework arXiv:2405.11143**Jian Hu, Xibin Wu, Wei Shen, et al.*2024 · 140 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-openrlhf-easy-use-scalable/)
3. [**Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models arXiv:2411.07140**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2024 · 34 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-chinese-simpleqa-chinese-factuality/)
4. **[Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2025 · 30 citations*
5. **[Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning ↗](https://arxiv.org/abs/2508.08221) arXiv:2508.08221 · no summary yet**Zihe Liu et al.*2025 · 15 citations*
6. **[Deconstructing Long Chain-of-Thought: A Structured Reasoning Optimization Framework for Long CoT Distillation ↗](https://arxiv.org/abs/2503.16385) arXiv:2503.16385 · no summary yet**Yijia Luo et al.*2025 · 14 citations*
7. **[The N+ Implementation Details of RLHF with PPO: A Case Study on TL;DR Summarization ↗](https://arxiv.org/abs/2403.17031) arXiv:2403.17031 · no summary yet**Shengyi Huang et al.*2024 · 14 citations*
8. **[GEM: A Gym for Agentic LLMs ↗](https://arxiv.org/abs/2510.01051) arXiv (Cornell University) · no summary yet**Liu, Zichen et al.*2025 · 6 citations*
9. **[ShopSimulator: Evaluating and Exploring RL-Driven LLM Agent for Shopping Assistants](https://md.research.elamur.ai/free/en/papers/wang-2026-shopsimulator-evaluating-exploring-rl-driven/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pei Wang, Yanan Wu, Xiaoshuai Song, et al.*2026 · 1 citation*
10. **[USB: A COMPREHENSIVE AND UNIFIED SAFETY EVALUATION BENCHMARK FOR MULTIMODAL LARGE LANGUAGE MODELS](https://md.research.elamur.ai/free/en/papers/zheng-2026-usb-comprehensive-unified-safety-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Baolin Zheng, Guanlin Chen, Qingyang Teng, et al.*2026 · 1 citation*

## Co-authors here

12 of 28 co-authors with a page, the most papers together first.

- [Jiaheng Liu](https://md.research.elamur.ai/free/en/authors/jiaheng-liu/) ×3
- [Shilong Li](https://md.research.elamur.ai/free/en/authors/shilong-li/) ×2
- [Wenbo Su](https://md.research.elamur.ai/free/en/authors/wenbo-su/) ×2
- [Xingyuan Bu](https://md.research.elamur.ai/free/en/authors/xingyuan-bu/) ×2
- [Xuepeng Liu](https://md.research.elamur.ai/free/en/authors/xuepeng-liu/) ×2
- [Yancheng He](https://md.research.elamur.ai/free/en/authors/yancheng-he/) ×2
- [Yingshui Tan](https://md.research.elamur.ai/free/en/authors/yingshui-tan/) ×2
- [Bin Chen](https://md.research.elamur.ai/free/en/authors/bin-chen/)
- [Bo Zheng](https://md.research.elamur.ai/free/en/authors/bo-zheng/)
- [Boren Zheng](https://md.research.elamur.ai/free/en/authors/boren-zheng/)
- [Ge Zhang](https://md.research.elamur.ai/free/en/authors/ge-zhang/)
- [Hangyu Guo](https://md.research.elamur.ai/free/en/authors/hangyu-guo/)

## 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/) ×2, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/)
- Proceedings of the AAAI Conference on Artificial Intelligence

## Cited by

Papers of our library cite their works 246 times (of the 149,439 papers whose bibliographies we read); [52 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/weixun-wang/cited-by/).

Updated 1 November 2026