31 citations · 31 across the 9 of their papers we have counts for
9 papers
Figma2Code: Automating Multimodal Design to Code in the Wild
Yi Gui, Jiawan Zhang, Yina Wang +9
Front-end development constitutes a substantial portion of software engineering, yet converting design mockups into production-ready User Interface (UI) code remains tedious and co…
Graph-Based Fraud Detection with Dual-Path Graph Filtering
Wei He, Wensheng Gan, Philip S. Yu
Fraud detection on graph data can be viewed as a demanding task that requires distinguishing between different types of nodes. Because graph neural networks (GNNs) are naturally su…
DeepSeek Robustness Against Semantic-Character Dual-Space Mutated Prompt Injection
Junyu Ren, Xingjian Pan, Wensheng Gan +1
Prompt injection has emerged as a critical security threat to large language models (LLMs), yet existing studies predominantly focus on single-dimensional attack strategies, such a…
GAM: Hierarchical Graph-based Agentic Memory for LLM Agents
Zhaofen Wu, Hanrong Zhang, Fulin Lin +9
To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining prior knowledge. Current uni…
FedRio: Personalized Federated Social Bot Detection via Cooperative Reinforced Contrastive Adversarial Distillation
Yingguang Yang, Hao Liu, Xin Zhang +8
Social bot detection is critical to the stability and security of online social platforms. However, current state-of-the-art bot detection models are largely developed in isolation…
Missing Pattern Tree based Decision Grouping and Ensemble for Enhancing Pair Utilization in Deep Incomplete Multi-View Clustering
Jie Xu, Wenyuan Yang, Yazhou Ren +3
Real-world multi-view data often exhibit highly inconsistent missing patterns, posing significant challenges for incomplete multi-view clustering (IMVC). Although existing IMVC met…
AgentDR: Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents
Mingdai Yang, Nurendra Choudhary, Jiangshu Du +4
Recent agent-based recommendation frameworks aim to simulate user behaviors by incorporating memory mechanisms and prompting strategies, but they struggle with hallucinating non-ex…
Update Selective Parameters: Federated Machine Unlearning Based on Model Explanation
Heng Xu, Tianqing Zhu, Lefeng Zhang +2
Federated learning is a promising privacy-preserving paradigm for distributed machine learning. In this context, there is sometimes a need for a specialized process called machine…
Deep Collaborative Embedding for information cascade prediction
Yuhui Zhao, Ning Yang, Tao Lin +1
Recently, information cascade prediction has attracted increasing interest from researchers, but it is far from being well solved partly due to the three defects of the existing wo…