Papers by Xiaokun Chen
FrontCoder: Scaling Visual Fidelity in Front-End Code Generation (2026.findings-acl)
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Jun Feng, Jian Yang, Wei Zhang, Jing Wang, Keyi Chen, Xiaokun Yang, Weicheng Gu, Yihang Lou, Yan Bai, Xianglong Liu
| Challenge: | Existing work on front-end code generation fails to provide visual fidelity and rendering quality for front- end developers. |
| Approach: | They propose a three-stage pipeline to enhance front-end code generation capabilities in LLMs . they use synthetic data, quality-controlled supervised fine-tuning, and reinforcement learning . |
| Outcome: | The proposed model achieves competitive performance with frontier models while maintaining generation efficiency. |
Detecting RAG Extraction Attack via Dual-Path Runtime Integrity Game (2026.acl-long)
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| Challenge: | Retrieval-Augmented Generation (RAG) systems augment large language models with external knowledge, but introduce a critical security vulnerability: Knowledge Base Leakage. |
| Approach: | They propose a runtime defense mechanism inspired by stack canaries in software security . canaryRAG embeds carefully designed canary tokens into retrieved chunks and reformulates RAG extraction defense as a dual-path runtime integrity game. |
| Outcome: | The proposed system can detect and prevent RAG Knowledge Base Leakage in real time . it can be integrated into arbitrary RAG pipelines without retraining or structural modifications . |