activity
20182025
most citedAsteria: Deep Learning-based AST-Encoding for Cross-platform Binary Code Similarity Detection

73 citations · 164 across the 14 of their papers we have counts for

collaborators

16 papers

cs.CR2025

Demystifying Feature Engineering in Malware Analysis of API Call Sequences

Tianheng Qu, Hongsong Zhu, Limin Sun +4

Machine learning (ML) has been widely used to analyze API call sequences in malware analysis, which typically requires the expertise of domain specialists to extract relevant featu…

cs.CL2023

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.…

cs.SE2023★ 1 cited

LibAM: An Area Matching Framework for Detecting Third-party Libraries in Binaries

Siyuan Li, Yongpan Wang, Chaopeng Dong +8

Third-party libraries (TPLs) are extensively utilized by developers to expedite the software development process and incorporate external functionalities. Nevertheless, insecure TP…

cs.CV2022★ 3 cited

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…

cs.CL2022

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…

cs.MM2022

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…