19 citations · 24 across the 14 of their papers we have counts for
16 papers
UNBIND: UNlearning By INference-time Directional Steering for Code LLMs
Zhengyang Shan, Jiayun Xin, Yanjun Lin +7
Code large language models acquire programming capabilities from large code corpora, but can also memorize implementations that later require removal. Code unlearning is needed to…
OBLIVION: Workflow-Level Operational Skill Unlearning for Deployed Agents
Zhengyang Shan, Xu Qian, Jiayun Xin +3
Large language model agents are becoming operational interfaces to files, memories, registries, and external tools. This deployment shift creates a new skill revocation problem: af…
Don't believe everything you read: Understanding and Measuring MCP Behavior under Misleading Tool Descriptions
Zhihao Li, Boyang Ma, Xuelong Dai +4
The Model Context Protocol (MCP) enables large language models to invoke external tools through natural-language descriptions, forming the foundation of many AI agent applications.…
"MCP Does Not Stand for Misuse Cryptography Protocol": Uncovering Cryptographic Misuse in Model Context Protocol at Scale
Biwei Yan, Yue Zhang, Minghui Xu +5
The Model Context Protocol (MCP) is rapidly emerging as the middleware for LLM-based applications, offering a standardized interface for tool integration. However, its built-in sec…
Dataset Ownership in the Era of Large Language Models
Kun Li, Cheng Wang, Minghui Xu +2
As datasets become critical assets in modern machine learning systems, ensuring robust copyright protection has emerged as an urgent challenge. Traditional legal mechanisms often f…
LIFT: Automating Symbolic Execution Optimization with Large Language Models for AI Networks
Ruoxi Wang, Kun Li, Minghui Xu +5
Dynamic Symbolic Execution (DSE) is a key technique in program analysis, widely used in software testing, vulnerability discovery, and formal verification. In distributed AI system…
We Urgently Need Privilege Management in MCP: A Measurement of API Usage in MCP Ecosystems
Zhihao Li, Kun Li, Boyang Ma +3
The Model Context Protocol (MCP) has emerged as a widely adopted mechanism for connecting large language models to external tools and resources. While MCP promises seamless extensi…
Can Large Language Models Be Trusted Paper Reviewers? A Feasibility Study
Chuanlei Li, Xu Hu, Minghui Xu +3
Academic paper review typically requires substantial time, expertise, and human resources. Large Language Models (LLMs) present a promising method for automating the review process…
Say What You Mean: Natural Language Access Control with Large Language Models for Internet of Things
Ye Cheng, Minghui Xu, Yue Zhang +7
Access control in the Internet of Things (IoT) is becoming increasingly complex, as policies must account for dynamic and contextual factors such as time, location, user behavior,…
Starfish: Rebalancing Multi-Party Off-Chain Payment Channels
Minghui Xu, Wenxuan Yu, Yuanzhe Zhang +7
Blockchain technology has revolutionized the way transactions are executed, but scalability remains a major challenge. Payment Channel Network (PCN), as a Layer-2 scaling solution,…
I'm Spartacus, No, I'm Spartacus: Measuring and Understanding LLM Identity Confusion
Kun Li, Shichao Zhuang, Yue Zhang +5
Large Language Models (LLMs) excel in diverse tasks such as text generation, data analysis, and software development, making them indispensable across domains like education, busin…
AutoIoT: Automated IoT Platform Using Large Language Models
Ye Cheng, Minghui Xu, Yue Zhang +3
IoT platforms, particularly smart home platforms providing significant convenience to people's lives such as Apple HomeKit and Samsung SmartThings, allow users to create automation…
A Treatment of EIP-1559: Enhancing Transaction Fee Mechanism through Nth-Price Auction
Kun Li, Guangpeng Qi, Guangyong Shang +3
With the widespread adoption of blockchain technology, the transaction fee mechanism (TFM) in blockchain systems has become a prominent research topic. An ideal TFM should satisfy…
DataSafe: Copyright Protection with PUF Watermarking and Blockchain Tracking
Xiaolong Xue, Guangyong Shang, Zhen Ma +4
Digital watermarking methods are commonly used to safeguard digital media copyrights by confirming ownership and deterring unauthorized use. However, without reliable third-party o…
On Protecting the Data Privacy of Large Language Models (LLMs): A Survey
Biwei Yan, Kun Li, Minghui Xu +4
Large language models (LLMs) are complex artificial intelligence systems capable of understanding, generating and translating human language. They learn language patterns by analyz…
Spatial Crowdsourcing Task Allocation Scheme for Massive Data with Spatial Heterogeneity
Kun Li, Shengling Wang, Hongwei Shi +2
Spatial crowdsourcing (SC) engages large worker pools for location-based tasks, attracting growing research interest. However, prior SC task allocation approaches exhibit limitatio…