🧑‍🔬 Fali Wang

🏛️ Affiliations

🎓Pennsylvania State UniversityState College · United States2023–2026 · 14 papersEducationEmploymentcurrent🏛️Chinese Academy of SciencesBeijing · China2020–2022 · 6 papers🔬Institute of Information EngineeringBeijing · China2020–2021 · 5 papers🎓University of Chinese Academy of SciencesBeijing · China2020–2022 · 4 papers

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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models (2025 · 37 citations)
   The authors examine whether the common recipe of supervised fine-tuning followed by reinforcement learning, popularised by DeepSeek-R1, also works for Large Vision-Language Models (LVLMs).
2. Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language Models (2026 · 1 citation)
   The paper asks whether someone holding only an image, with no caption, can tell if that image was in the training data of a large vision-language model (LVLM).
3. Graph-Assisted Large Language Models: A Perspective on Mitigating Intrinsic Limitations (2026)
   This survey asks how graph structures can offset three built-in weaknesses of large language models. The first is knowledge: static training leads to outdated facts, errors, and unwanted memorization. The second is reasoning: token-by-token generation produces linear chains that cannot branch or backtrack. The third…

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness ↗arXiv:2411.03350 · no summary yetFali Wang et al.2024 · 159 citations
2. SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language ModelsarXiv:2504.11468Hardy Chen, Haoqin Tu, Fali Wang, et al.2025 · 37 citations
3. Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Zongyu Wu, Minhua Lin, Zhiwei Zhang, et al.2026 · 1 citation
4. Graph-Assisted Large Language Models: A Perspective on Mitigating Intrinsic LimitationsFindings of the Association for Computational LinguisticsHaitong Luo, Fali Wang, Weiyao Zhang, et al.2026

🤝 Co-authors here

12 of 13 co-authors with a page, the most papers together first.

• Hui Liu ×2
• Minhua Lin ×2
• Suhang Wang ×2
• Xianfeng Tang ×2
• Xianren Zhang ×2
• Zhiwei Zhang ×2
• Cihang Xie
• Haoqin Tu
• Hardy Chen
• Jiahao Zhang
• Qi He
• Xiang Zhang

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Conference of the European Chapter of the Association for Computational Linguistics (EACL): EACL 2026
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026

🔗 Cited by

Papers of our library cite their works 98 times (of the 149,439 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated 1 November 2026

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