CV

Master’s Student | Wang Xuan Institute of Computer Technology, Peking University (Sep 2024 - Present) My research focuses on AI for Security, Binary Analysis, and LLM Alignment and Reasoning Optimization. Deeply engaged in both academia and the tech industry, I am dedicated to leveraging artificial intelligence to solve fundamental system security challenges.

Academic & Research Background

Core Research Affiliations

• Wang Xuan Institute of Computer Technology, Peking University

  Core Member

  • Advisor: Prof. Xinhui Han
  • Research Focus: AI-empowered system security, intelligent attack and defense strategies, and adversarial attack research.

• VUL337 Group, Tsinghua University

  Visiting Master’s Student & Core Developer

  • Advisor: Prof. Chao Zhang
  • Key Contributions: Leading the indirect call (ICall) recognition project CALLEE and cross-architecture Binary Code Similarity Detection (BCSD); advancing controlled code generation and Machine Large Language Model (MLM) decompiler training; and developing software translation agents.

Education

• Peking University

  M.S. in Intelligent Science and Technology (2024 - Present)

• Beijing University of Posts and Telecommunications (BUPT)

  B.S. in Automation (2020 - 2024)

Internship Experience

Alibaba | AAGI Research Intern

• Core Responsibilities: Focused on Large Language Model (LLM) alignment, specifically designing Process Reward Models (PRM) and self-evolving mechanisms to enhance complex reasoning capabilities.
• Technical Achievements: Engineered and deployed process-level reward models integrated with reinforcement learning algorithms (such as GRPO) to provide granular, step-by-step supervision for multi-turn reasoning and tool-integrated tasks.
• Expertise: Developed a self-evolving framework that leverages automated verification and continuous feedback loops, enabling the model to autonomously iterate and optimize its reasoning policy without extensive human annotation.

ByteDance | Seed Talent Program - Seedance Intern

• Core Responsibilities: Model training and architecture development (Infra).
• Technical Achievements: Developed distributed training systems based on the Ray framework supporting large-scale training across thousands of GPUs. Gained extensive experience adapting and optimizing diverse heterogeneous computing platforms, including Huawei Ascend, H20, L20, and A100.
• Expertise: Provided deep technical support and strategy iteration for the model post-training pipeline.

Tencent - Yuanbao | Post-Training Intern

• Core Responsibilities: Focused on model alignment and reasoning capability enhancement during the LLM post-training phase.
• Tech Stack: Applied cutting-edge algorithms such as Supervised Fine-Tuning (SFT) and Reinforcement Learning alignment (e.g., PPO/GRPO) in production environments.

Huaqing Weiyang | Security Research Intern

• Core Achievements: Led the fine-tuning research of Qwen-3 for binary security applications.
• Academic Output: Proposed an innovative approach for cross-architecture code similarity detection. The research findings have been accepted by AAAI 2026 (CCF-A).

Research Skills & Expertise

• Binary Security: Cross-architecture function similarity detection, Indirect Call (ICall) recognition, and decompiler evaluation.
• Large Language Models: RLHF/GRPO implementation, Process Reward Models (PRM), and tool-integrated reasoning.
• System Architecture: Large-scale GPU cluster scheduling (Ray) and low-level Instruction Set Architecture (Cross-ISA) mapping analysis.

Publications

BDLF-Qwen3: Enhanced Cross-Architecture Binary Function Similarity Detection Through Binary Dynamic Layer Fusion

Y Wang, J Zhou, X Han, C Zhang. (2026). "BDLF-Qwen3: Enhanced Cross-Architecture Binary Function Similarity Detection Through Binary Dynamic Layer Fusion." The Fortieth AAAI Conference on Artificial Intelligence (AAAI-26).

PTC: Prefix Tuning CodeT5 for High-Quality Secure Network Measurement Script Generation

Y Wang, X Han. (2025). "PTC: Prefix Tuning CodeT5 for High-Quality Secure Network Measurement Script Generation." 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks.

DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios

Z Gao, Y Cui, H Wang, S Qin, Y Wang, B Zhang, C Zhang. (2025). "DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios." arXiv preprint arXiv:2505.11340.

CALLEE: Recovering Call Graphs for Binaries with Transfer and Contrastive Learning

W Zhu, Y Wang, Y Cui, C Zhang, X Han. (2025). "CALLEE: Recovering Call Graphs for Binaries with Transfer and Contrastive Learning." IEEE Transactions on Dependable and Secure Computing.

Virtual compiler is all you need for assembly code search

Z Gao, H Wang, Y Wang, C Zhang. (2024). "Virtual compiler is all you need for assembly code search." Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics.

AMP-EBiLSTM: employing novel deep learning strategies for the accurate prediction of antimicrobial peptides

Y Wang, L Wang, C Li, Y Pei, X Liu, Y Tian. (2023). "AMP-EBiLSTM: employing novel deep learning strategies for the accurate prediction of antimicrobial peptides." Frontiers in genetics. 14, 1232117.

Awards and Honors

• National College Mathematics Competition: 2nd Prize (13th), 3rd Prize (14th)
• Beijing Mathematics Competition: 1st Prize (32nd), 2nd Prize (33rd)
• Beijing Outstanding Graduate, BUPT Outstanding Graduate
• Beijing 2022 Winter Olympics & Paralympics Outstanding Volunteer
• Multiple academic scholarships and “Three Good Students” awards