9 citations · 21 across the 21 of their papers we have counts for
23 papers
Improving Adversarial Transferability on Vision-Language Pre-training Models via Surrogate-Specific Bias Correction
Lijia Yu, Jiuxin Cao, Yuchen Qiang +3
Adversarial examples reveal vulnerabilities in Vision-Language Pre-training (VLP) models and provide insights for improving robustness. A key property is cross-model transferabilit…
EvoRubric: Self-Evolving Rubric-Driven RL for Open-Ended Generation
Xin Guan, Xiaomeng Hu, Shen Huang +6
Reinforcement Learning (RL) has advanced Large Language Models (LLMs) in verifiable domains, while open-ended generation remains challenging due to the absence of definitive reward…
ViewSAM: Learning View-aware Cross-modal Semantics for Weakly Supervised Cross-view Referring Multi-Object Tracking
Jiawei Ge, Xintian Zhang, Jiuxin Cao +9
Cross-view Referring Multi-Object Tracking (CRMOT) aims to track multiple objects specified by natural language across multiple camera views, with globally consistent identities. D…
DyTopo: Dynamic Topology Routing for Multi-Agent Reasoning via Semantic Matching
Yuxing Lu, Yucheng Hu, Xukai Zhao +1
Multi-agent systems built from prompted large language models can improve multi-round reasoning, yet most existing pipelines rely on fixed, trajectory-wide communication patterns t…
Evidence-Augmented Policy Optimization with Reward Co-Evolution for Long-Context Reasoning
Xin Guan, Zijian Li, Shen Huang +3
While Reinforcement Learning (RL) has advanced LLM reasoning, applying it to long-context scenarios is hindered by sparsity of outcome rewards. This limitation fails to penalize un…
Debate-Enhanced Pseudo Labeling and Frequency-Aware Progressive Debiasing for Weakly-Supervised Camouflaged Object Detection with Scribble Annotations
Jiawei Ge, Jiuxin Cao, Xinyi Li +5
Weakly-Supervised Camouflaged Object Detection (WSCOD) aims to locate and segment objects that are visually concealed within their surrounding scenes, relying solely on sparse supe…
Denoise-then-Retrieve: Text-Conditioned Video Denoising for Video Moment Retrieval
Weijia Liu, Jiuxin Cao, Bo Miao +6
Current text-driven Video Moment Retrieval (VMR) methods encode all video clips, including irrelevant ones, disrupting multimodal alignment and hindering optimization. To this end,…
MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability
Weiqi Wu, Xin Guan, Shen Huang +6
Retrieval-Augmented Language Models (RALMs) represent a classic paradigm where models enhance generative capabilities using external knowledge retrieved via a specialized module. R…
External Reliable Information-enhanced Multimodal Contrastive Learning for Fake News Detection
Biwei Cao, Qihang Wu, Jiuxin Cao +2
With the rapid development of the Internet, the information dissemination paradigm has changed and the efficiency has been improved greatly. While this also brings the quick spread…
Positive Text Reframing under Multi-strategy Optimization
Shutong Jia, Biwei Cao, Qingqing Gao +2
Differing from sentiment transfer, positive reframing seeks to substitute negative perspectives with positive expressions while preserving the original meaning. With the emergence…
Context-Enhanced Video Moment Retrieval with Large Language Models
Weijia Liu, Bo Miao, Jiuxin Cao +4
Current methods for Video Moment Retrieval (VMR) struggle to align complex situations involving specific environmental details, character descriptions, and action narratives. To ta…
Community Detection for Heterogeneous Multiple Social Networks
Ziqing Zhu, Guan Yuan, Tao Zhou +1
The community plays a crucial role in understanding user behavior and network characteristics in social networks. Some users can use multiple social networks at once for a variety…
VAEMax: Open-Set Intrusion Detection based on OpenMax and Variational Autoencoder
Zhiyin Qiu, Ding Zhou, Yahui Zhai +3
Promptly discovering unknown network attacks is critical for reducing the risk of major loss imposed on system or equipment. This paper aims to develop an open-set intrusion detect…
Query-Based Knowledge Sharing for Open-Vocabulary Multi-Label Classification
Xuelin Zhu, Jian Liu, Dongqi Tang +4
Identifying labels that did not appear during training, known as multi-label zero-shot learning, is a non-trivial task in computer vision. To this end, recent studies have attempte…
Text as Image: Learning Transferable Adapter for Multi-Label Classification
Xuelin Zhu, Jiuxin Cao, Jian liu +7
Pre-trained vision-language models have notably accelerated progress of open-world concept recognition. Their impressive zero-shot ability has recently been transferred to multi-la…
Beyond Visual Cues: Synchronously Exploring Target-Centric Semantics for Vision-Language Tracking
Jiawei Ge, Xiangmei Chen, Jiuxin Cao +2
Single object tracking aims to locate one specific target in video sequences, given its initial state. Classical trackers rely solely on visual cues, restricting their ability to h…
Causal-Story: Local Causal Attention Utilizing Parameter-Efficient Tuning For Visual Story Synthesis
Tianyi Song, Jiuxin Cao, Kun Wang +2
The excellent text-to-image synthesis capability of diffusion models has driven progress in synthesizing coherent visual stories. The current state-of-the-art method combines the f…
Multi-hop Commonsense Knowledge Injection Framework for Zero-Shot Commonsense Question Answering
Xin Guan, Biwei Cao, Qingqing Gao +3
Commonsense question answering (QA) research requires machines to answer questions based on commonsense knowledge. However, this research requires expensive labor costs to annotate…
No Place to Hide: Dual Deep Interaction Channel Network for Fake News Detection based on Data Augmentation
Biwei Cao, Lulu Hua, Jiuxin Cao +3
Online Social Network (OSN) has become a hotbed of fake news due to the low cost of information dissemination. Although the existing methods have made many attempts in news content…
AlignVE: Visual Entailment Recognition Based on Alignment Relations
Biwei Cao, Jiuxin Cao, Jie Gui +5
Visual entailment (VE) is to recognize whether the semantics of a hypothesis text can be inferred from the given premise image, which is one special task among recent emerged visio…
Understanding User Topic Preferences across Multiple Social Networks
Ziqing Zhu, Jiuxin Cao, Tao Zhou +2
In recent years, social networks have shown diversity in function and applications. People begin to use multiple online social networks simultaneously for different demands. The ab…
Heterogeneous Hypergraph Embedding for Graph Classification
Xiangguo Sun, Hongzhi Yin, Bo Liu +4
Recently, graph neural networks have been widely used for network embedding because of their prominent performance in pairwise relationship learning. In the real world, a more natu…
Community Detection Across Multiple Social Networks based on Overlapping Users
Ziqing Zhu, Tao Zhou, Chenghao Jia +2
With the rapid development of Internet technology, online social networks (OSNs) have got fast development and become increasingly popular. Meanwhile, the research works across mul…