Scholar
Xuhong Wang
Google Scholar ID: qBfqJbcAAAAJ
Shanghai Artificial Intelligence Laboratory
Citations & Impact
Citations
1,074
H-index
13
i10-index
15
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- 2025.11: Published C2RM, a large model RL reward model based on uncertainty modeling, at EMNLP 2025 Main (Oral).
- 2025.8: Released PiKV, a distributed KV Cache architecture for MoE model optimization.
- 2025.8: Released VRPRM, a state-of-the-art CoT-PRM model.
- 2025.8: Released NaviMaster, a unified model capable of operating both digital GUI interfaces and real-world navigation.
- 2025.7: As Core Lead, responsible for the knowledge enhancement and 'Prudent Mode' modules of SafeWork-R1.
- 2025.6: Guided an intern to submit a paper accepted by ICCV2025, achieving SOTA results in multimodal retrieval.
- 2025.5: Published a review article on AI provenance in the Artificial Intelligence Review journal.
- 2023.10: First author of a paper using dynamic graph network evolution engines for accelerating complex traffic system simulations.
- 2022.10: Joined Shanghai AI Lab as a young researcher, with excellent performance evaluations for two consecutive years.
- 2022.11: First-author paper accepted at the first Learning on Graphs Conference.
- 2022.3: Co-authored a paper published in Nature Machine Intelligence.
- 2021.9: First-author graph computing paper accepted at SIGMOD 2021 Oral.
- 2020.2: First paper published in the Knowledge-Based Systems journal.
Research Experience
- Joined the Secure and Trustworthy AI Center of Shanghai AI Lab in October 2024, responsible for enhancing the trustworthiness of large models with knowledge. Started working as a young researcher at Shanghai AI Lab in October 2022, mainly focusing on optimizing AI security evaluation systems and multi-agent simulation platforms.
Education
- Received a bachelor's degree in Electronic Information Engineering from Sichuan University in 2017; obtained a Ph.D. in Artificial Intelligence from Shanghai Jiao Tong University in 2022.
Background
- A young researcher at Shanghai AI Lab, focusing on graph computing and knowledge mining. Currently, his research is centered around developing self-evolving, trustworthy multimodal agents.
Miscellany
- Interests include multimodal large language models, self-evolving memory systems, and environment feedback reinforcement learning.
Co-authors