198 citations · 220 across the 29 of their papers we have counts for
30 papers
Offline-Online Curriculum RL for Multimodal Reasoning
Wendi Deng, Hang Du, Guoshun Nan +11
Multimodal large language models exhibit capabilities on reasoning tasks, yet often produce flawed intermediate steps while yielding correct final answers. This behavior undermines…
SelPE: Progressive Selection for Private Structured Text Synthesis
Xuancheng Zhu, Guoshun Nan, Han Zhang +6
Many data-driven applications rely on structured textual records, such as clinical triage notes and financial transaction logs, for downstream learning and decision-making. In priv…
AutoRAS: Learning Robust Agentic Systems with Primitive Representations
Yang Yue, Xuancheng Zhu, Yuyang Ma +7
The automated design of agentic systems offers a promising pathway for scaling large language models (LLMs) beyond single-agent reasoning. While prior work has advanced task perfor…
See First, Answer Later: Visual Evidence Pre-Alignment via Sufficiency-Driven RL
Yilian Liu, Sicong Leng, Guoshun Nan +7
Multimodal large language models (MLLMs) integrate strong text reasoning with visual inputs, yet their responses can be inconsistent with the underlying images, indicating ineffect…
Can LLM Agents Sustain Long-Horizon Organizational Dynamics?
Xuancheng Zhu, Yang Yue, Shuaibing Wan +4
Large language agents are increasingly used for social simulation, yet it remains unclear whether they can sustain coherent behavior in structured organizations, where goals must p…
Enhancing Cloud Network Resilience via a Robust LLM-Empowered Multi-Agent Reinforcement Learning Framework
Yixiao Peng, Hao Hu, Feiyang Li +5
While virtualization and resource pooling empower cloud networks with structural flexibility and elastic scalability, they inevitably expand the attack surface and challenge cyber…
Sensing and Understanding the World over Air: A Large Multimodal Model for Mobile Networks
Zhuoran Duan, Yuhao Wei, Guoshun Nan +9
Large models (LMs), such as ChatGPT, have made a significant impact across diverse domains and hold great potential to facilitate the evolution of network intelligence. Wireless-na…
Advancing Compositional LLM Reasoning with Structured Task Relations in Interactive Multimodal Communications
Xinye Cao, Hongcan Guo, Guoshun Nan +9
Interactive multimodal applications (IMAs), such as route planning in the Internet of Vehicles, enrich users' personalized experiences by integrating various forms of data over wir…
Generative Diffusion Models for Wireless Networks: Fundamental, Architecture, and State-of-the-Art
Dayu Fan, Rui Meng, Xiaodong Xu +9
With the rapid development of Generative Artificial Intelligence (GAI) technology, Generative Diffusion Models (GDMs) have shown significant empowerment potential in the field of w…
Agile Orchestration at Will: An Entire Smart Service-Based Security Architecture Towards 6G
Zhuoran Duan, Guoshun Nan, Rushan Li +8
The upcoming 6G will fundamentally reshape mobile networks beyond communications, unlocking a multitude of applications that were once considered unimaginable. Meanwhile, security…
A Novel Indicator for Quantifying and Minimizing Information Utility Loss of Robot Teams
Xiyu Zhao, Qimei Cui, Wei Ni +5
The timely exchange of information among robots within a team is vital, but it can be constrained by limited wireless capacity. The inability to deliver information promptly can re…
Two Is Better Than One: Rotations Scale LoRAs
Hongcan Guo, Guoshun Nan, Yuan Yang +9
Scaling Low-Rank Adaptation (LoRA)-based Mixture-of-Experts (MoE) facilitates large language models (LLMs) to efficiently adapt to diverse tasks. However, traditional gating mechan…
An LLM-based Self-Evolving Security Framework for 6G Space-Air-Ground Integrated Networks
Qi Qin, Xinye Cao, Guoshun Nan +8
Recently emerged 6G space-air-ground integrated networks (SAGINs), which integrate satellites, aerial networks, and terrestrial communications, offer ubiquitous coverage for variou…
Generative AI for Physical-Layer Authentication
Rui Meng, Xiqi Cheng, Song Gao +6
Recently, Artificial Intelligence (AI)-driven Physical-Layer Authentication (PLA), which focuses on achieving endogenous security and intelligent identity authentication, has attra…
Refining Positive and Toxic Samples for Dual Safety Self-Alignment of LLMs with Minimal Human Interventions
Jingxin Xu, Guoshun Nan, Sheng Guan +7
Recent AI agents, such as ChatGPT and LLaMA, primarily rely on instruction tuning and reinforcement learning to calibrate the output of large language models (LLMs) with human inte…
Exploring What Why and How: A Multifaceted Benchmark for Causation Understanding of Video Anomaly
Hang Du, Guoshun Nan, Jiawen Qian +7
Recent advancements in video anomaly understanding (VAU) have opened the door to groundbreaking applications in various fields, such as traffic monitoring and industrial automation…
Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities
Qimei Cui, Xiaohu You, Ni Wei +22
With the growing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and sixth-generation (6G) communication networks ha…
MALSIGHT: Exploring Malicious Source Code and Benign Pseudocode for Iterative Binary Malware Summarization
Haolang Lu, Hongrui Peng, Guoshun Nan +6
Binary malware summarization aims to automatically generate human-readable descriptions of malware behaviors from executable files, facilitating tasks like malware cracking and det…
ContextBLIP: Doubly Contextual Alignment for Contrastive Image Retrieval from Linguistically Complex Descriptions
Honglin Lin, Siyu Li, Guoshun Nan +8
Image retrieval from contextual descriptions (IRCD) aims to identify an image within a set of minimally contrastive candidates based on linguistically complex text. Despite the suc…
Uncovering What, Why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly
Hang Du, Sicheng Zhang, Binzhu Xie +16
Video anomaly understanding (VAU) aims to automatically comprehend unusual occurrences in videos, thereby enabling various applications such as traffic surveillance and industrial…
Semantic Entropy Can Simultaneously Benefit Transmission Efficiency and Channel Security of Wireless Semantic Communications
Yankai Rong, Guoshun Nan, Minwei Zhang +9
Recently proliferated deep learning-based semantic communications (DLSC) focus on how transmitted symbols efficiently convey a desired meaning to the destination. However, the sens…
Can We Improve Channel Reciprocity via Loop-back Compensation for RIS-assisted Physical Layer Key Generation
Ningya Xu, Guoshun Nan, Xiaofeng Tao +3
Reconfigurable intelligent surface (RIS) facilitates the extraction of unpredictable channel features for physical layer key generation (PKG), securing communications among legitim…
Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks
Chenyang Qiu, Guoshun Nan, Tianyu Xiong +6
Graph convolution networks (GCNs) are extensively utilized in various graph tasks to mine knowledge from spatial data. Our study marks the pioneering attempt to quantitatively inve…
DocMSU: A Comprehensive Benchmark for Document-level Multimodal Sarcasm Understanding
Hang Du, Guoshun Nan, Sicheng Zhang +6
Multimodal Sarcasm Understanding (MSU) has a wide range of applications in the news field such as public opinion analysis and forgery detection. However, existing MSU benchmarks an…