5 citations · 8 across the 9 of their papers we have counts for
9 papers
Understanding Binary Code Similarity for Real-World Vulnerability Detection: A Large-Scale Empirical Study
Jingdong Guo, Chaopeng Dong, Yimo Ren +4
Firmware lies at the heart of IoT devices. Its development depends heavily on third-party libraries (TPLs), which greatly accelerate the process but simultaneously introduce associ…
Lares: LLM-driven Code Slice Semantic Search for Patch Presence Testing
Siyuan Li, Yaowen Zheng, Hong Li +7
In modern software ecosystems, 1-day vulnerabilities pose significant security risks due to extensive code reuse. Identifying vulnerable functions in target binaries alone is insuf…
SMTFL: Secure Model Training to Untrusted Participants in Federated Learning
Zhihui Zhao, Xiaorong Dong, Yimo Ren +4
Federated learning is an essential distributed model training technique. However, threats such as gradient inversion attacks and poisoning attacks pose significant risks to the pri…
Hierarchical Aligned Multimodal Learning for NER on Tweet Posts
Peipei Liu, Hong Li, Yimo Ren +4
Mining structured knowledge from tweets using named entity recognition (NER) can be beneficial for many down stream applications such as recommendation and intention understanding.…
Multi-Granularity Cross-Modality Representation Learning for Named Entity Recognition on Social Media
Peipei Liu, Gaosheng Wang, Hong Li +4
Named Entity Recognition (NER) on social media refers to discovering and classifying entities from unstructured free-form content, and it plays an important role for various applic…
CEntRE: A paragraph-level Chinese dataset for Relation Extraction among Enterprises
Peipei Liu, Hong Li, Zhiyu Wang +5
Enterprise relation extraction aims to detect pairs of enterprise entities and identify the business relations between them from unstructured or semi-structured text data, and it i…
Improving the Modality Representation with Multi-View Contrastive Learning for Multimodal Sentiment Analysis
Peipei Liu, Xin Zheng, Hong Li +4
Modality representation learning is an important problem for multimodal sentiment analysis (MSA), since the highly distinguishable representations can contribute to improving the a…
Multi-features based Semantic Augmentation Networks for Named Entity Recognition in Threat Intelligence
Peipei Liu, Hong Li, Zuoguang Wang +3
Extracting cybersecurity entities such as attackers and vulnerabilities from unstructured network texts is an important part of security analysis. However, the sparsity of intellig…
Threat Detection for General Social Engineering Attack Using Machine Learning Techniques
Zuoguang Wang, Yimo Ren, Hongsong Zhu +1
This paper explores the threat detection for general Social Engineering (SE) attack using Machine Learning (ML) techniques, rather than focusing on or limited to a specific SE atta…