Weixun Wang
Weixun Wang has 5 papers in our library, in 2024–2026, most of them on Language models & pretraining, Evaluation & benchmarks, Reasoning; often with Jiaheng Liu, Shilong Li, Wenbo Su.
OpenAlex · ORCID · h-index 22 · 101 works · 2,737 citations OpenAlex, 2026-10-14
📄 5 works in our library · 🔗 Cited 246 times in our library · 5 more in our library without a page yet · ⭐ Paper Stars ranking: #5637
Affiliations
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 5 worksArtificial Intelligence · 5 worksArts and Humanities · 4 worksLanguage and Linguistics · 4 worksComputer Vision and Pattern Recognition · 1 workInformation Systems · 1 work
🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 3 worksReasoning · 1 workBias, fairness & safety · 1 workEvaluation & benchmarks · 1 workVision & language · 1 work
Works by year
2020s
Papers
- OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework (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… - Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models (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… - Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning? (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… - ShopSimulator: Evaluating and Exploring RL-Driven LLM Agent for Shopping Assistants (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. - USB: A COMPREHENSIVE AND UNIFIED SAFETY EVALUATION BENCHMARK FOR MULTIMODAL LARGE LANGUAGE MODELS (2026 · 1 citation)
Existing safety benchmarks for multimodal large language models (MLLMs) cover few risk types and contain few samples.
All works
- Multi-Agent Game Abstraction via Graph Attention Neural Network ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetYong Liu et al.2020 · 247 citations
- OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF FrameworkarXiv:2405.11143Jian Hu, Xibin Wu, Wei Shen, et al.2024 · 140 citations
- Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language ModelsarXiv:2411.07140Yancheng He, Shilong Li, Jiaheng Liu, et al.2024 · 34 citations
- Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?Annual Meeting of the Association for Computational Linguistics (ACL)Yancheng He, Shilong Li, Jiaheng Liu, et al.2025 · 30 citations
- Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning ↗arXiv:2508.08221 · no summary yetZihe Liu et al.2025 · 15 citations
- Deconstructing Long Chain-of-Thought: A Structured Reasoning Optimization Framework for Long CoT Distillation ↗arXiv:2503.16385 · no summary yetYijia Luo et al.2025 · 14 citations
- The N+ Implementation Details of RLHF with PPO: A Case Study on TL;DR Summarization ↗arXiv:2403.17031 · no summary yetShengyi Huang et al.2024 · 14 citations
- GEM: A Gym for Agentic LLMs ↗arXiv (Cornell University) · no summary yetLiu, Zichen et al.2025 · 6 citations
- ShopSimulator: Evaluating and Exploring RL-Driven LLM Agent for Shopping AssistantsAnnual Meeting of the Association for Computational Linguistics (ACL)Pei Wang, Yanan Wu, Xiaoshuai Song, et al.2026 · 1 citation
- USB: A COMPREHENSIVE AND UNIFIED SAFETY EVALUATION BENCHMARK FOR MULTIMODAL LARGE LANGUAGE MODELSAnnual Meeting of the Association for Computational Linguistics (ACL)Baolin Zheng, Guanlin Chen, Qingyang Teng, et al.2026 · 1 citation
Co-authors here
- Jiaheng Liu ×3
- Shilong Li ×2
- Wenbo Su ×2
- Xingyuan Bu ×2
- Xuepeng Liu ×2
- Yancheng He ×2
- Yingshui Tan ×2
- Bin Chen
- Bo Zheng
- Boren Zheng
- Ge Zhang
- Hangyu Guo
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×3: ACL 2026 ×2, ACL 2025
- Proceedings of the AAAI Conference on Artificial Intelligence
Cited by
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