550 citations · 824 across the 21 of their papers we have counts for
21 papers
Sparse Evidence Can Suffice: Agentic Evidence Seeking for Multimodal Video Misinformation Detection
Haochen Zhao, Yongxiu Xu, Xinkui Lin +6
Multimodal video misinformation detection is commonly formulated as a holistic video-understanding task, where the entire video and its associated content are processed and judged…
Does Unification Come at a Cost? Uni-SafeBench: A Safety Benchmark for Unified Multimodal Large Models
Zixiang Peng, Yongxiu Xu, Qin-Yi Zhang +5
Unified Multimodal Large Models (UMLMs) integrate understanding and generation capabilities within a single architecture. While unified architectures expand multimodal capabilities…
From Scale to Speed: Adaptive Test-Time Scaling for Image Editing
Xiangyan Qu, Zhenlong Yuan, Jing Tang +9
Image Chain-of-Thought (Image-CoT) is a test-time scaling paradigm that improves image generation by extending inference time. Most Image-CoT methods focus on text-to-image (T2I) g…
MalRAG: A Retrieval-Augmented LLM Framework for Open-set Malicious Traffic Identification
Xiang Luo, Chang Liu, Gang Xiong +4
Fine-grained identification of IDS-flagged suspicious traffic is crucial in cybersecurity. In practice, cyber threats evolve continuously, making the discovery of novel malicious t…
MMSD3.0: A Multi-Image Benchmark for Real-World Multimodal Sarcasm Detection
Haochen Zhao, Yuyao Kong, Yongxiu Xu +4
Despite progress in multimodal sarcasm detection, existing datasets and methods predominantly focus on single-image scenarios, overlooking potential semantic and affective relation…
T2VParser: Adaptive Decomposition Tokens for Partial Alignment in Text to Video Retrieval
Yili Li, Gang Xiong, Gaopeng Gou +4
Text-to-video retrieval essentially aims to train models to align visual content with textual descriptions accurately. Due to the impressive general multimodal knowledge demonstrat…
Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification
Xinjie Lin, Gang Xiong, Gaopeng Gou +4
Encrypted traffic classification is highly challenging in network security due to the need for extracting robust features from content-agnostic traffic data. Existing approaches fa…
DecETT: Accurate App Fingerprinting Under Encrypted Tunnels via Dual Decouple-based Semantic Enhancement
Zheyuan Gu, Chang Liu, Xiyuan Zhang +5
Due to the growing demand for privacy protection, encrypted tunnels have become increasingly popular among mobile app users, which brings new challenges to app fingerprinting (AF)-…
Missing Target-Relevant Information Prediction with World Model for Accurate Zero-Shot Composed Image Retrieval
Yuanmin Tang, Jing Yu, Keke Gai +4
Zero-Shot Composed Image Retrieval (ZS-CIR) involves diverse tasks with a broad range of visual content manipulation intent across domain, scene, object, and attribute. The key cha…
MADS: Multi-Attribute Document Supervision for Zero-Shot Image Classification
Xiangyan Qu, Jing Yu, Jiamin Zhuang +3
Zero-shot learning (ZSL) aims to train a model on seen classes and recognize unseen classes by knowledge transfer through shared auxiliary information. Recent studies reveal that d…
ProAPO: Progressively Automatic Prompt Optimization for Visual Classification
Xiangyan Qu, Gaopeng Gou, Jiamin Zhuang +5
Vision-language models (VLMs) have made significant progress in image classification by training with large-scale paired image-text data. Their performances largely depend on the p…
Reason-before-Retrieve: One-Stage Reflective Chain-of-Thoughts for Training-Free Zero-Shot Composed Image Retrieval
Yuanmin Tang, Xiaoting Qin, Jue Zhang +7
Composed Image Retrieval (CIR) aims to retrieve target images that closely resemble a reference image while integrating user-specified textual modifications, thereby capturing user…
Denoise-I2W: Mapping Images to Denoising Words for Accurate Zero-Shot Composed Image Retrieval
Yuanmin Tang, Jing Yu, Keke Gai +4
Zero-Shot Composed Image Retrieval (ZS-CIR) supports diverse tasks with a broad range of visual content manipulation intentions that can be related to domain, scene, object, and at…
Visual-Semantic Decomposition and Partial Alignment for Document-based Zero-Shot Learning
Xiangyan Qu, Jing Yu, Keke Gai +5
Recent work shows that documents from encyclopedias serve as helpful auxiliary information for zero-shot learning. Existing methods align the entire semantics of a document with co…
TTAGN: Temporal Transaction Aggregation Graph Network for Ethereum Phishing Scams Detection
Sijia Li, Gaopeng Gou, Chang Liu +3
In recent years, phishing scams have become the most serious type of crime involved in Ethereum, the second-largest blockchain platform. The existing phishing scams detection techn…
6GAN: IPv6 Multi-Pattern Target Generation via Generative Adversarial Nets with Reinforcement Learning
Tianyu Cui, Gaopeng Gou, Gang Xiong +3
Global IPv6 scanning has always been a challenge for researchers because of the limited network speed and computational power. Target generation algorithms are recently proposed to…
A Comprehensive Study of Accelerating IPv6 Deployment
Tianyu Cui, Chang Liu, Gaopeng Gou +2
Since the lack of IPv6 network development, China is currently accelerating IPv6 deployment. In this scenario, traffic and network structure show a huge shift. However, due to the…
SiamHAN: IPv6 Address Correlation Attacks on TLS Encrypted Traffic via Siamese Heterogeneous Graph Attention Network
Tianyu Cui, Gaopeng Gou, Gang Xiong +3
Unlike IPv4 addresses, which are typically masked by a NAT, IPv6 addresses could easily be correlated with user activity, endangering their privacy. Mitigations to address this pri…
6GCVAE: Gated Convolutional Variational Autoencoder for IPv6 Target Generation
Tianyu Cui, Gaopeng Gou, Gang Xiong
IPv6 scanning has always been a challenge for researchers in the field of network measurement. Due to the considerable IPv6 address space, while recent network speed and computatio…
ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification
Xinjie Lin, Gang Xiong, Gaopeng Gou +3
Encrypted traffic classification requires discriminative and robust traffic representation captured from content-invisible and imbalanced traffic data for accurate classification,…
6VecLM: Language Modeling in Vector Space for IPv6 Target Generation
Tianyu Cui, Gang Xiong, Gaopeng Gou +2
Fast IPv6 scanning is challenging in the field of network measurement as it requires exploring the whole IPv6 address space but limited by current computational power. Researchers…