48 citations · 53 across the 8 of their papers we have counts for
8 papers
Prefix Probing: Lightweight Harmful Content Detection for Large Language Models
Jirui Yang, Hengqi Guo, Zhihui Lu +6
Large language models often face a three-way trade-off among detection accuracy, inference latency, and deployment cost when used in real-world safety-sensitive applications. This…
Can LLM Infer Risk Information From MCP Server System Logs?
Jiayi Fu, Yuansen Zhang, Yinggui Wang
Large Language Models (LLMs) demonstrate strong capabilities in solving complex tasks when integrated with external tools. The Model Context Protocol (MCP) has become a standard in…
PRIV-QA: Privacy-Preserving Question Answering for Cloud Large Language Models
Guangwei Li, Yuansen Zhang, Yinggui Wang +3
The rapid development of large language models (LLMs) is redefining the landscape of human-computer interaction, and their integration into various user-service applications is bec…
CodeChameleon: Personalized Encryption Framework for Jailbreaking Large Language Models
Huijie Lv, Xiao Wang, Yuansen Zhang +6
Adversarial misuse, particularly through `jailbreaking' that circumvents a model's safety and ethical protocols, poses a significant challenge for Large Language Models (LLMs). Thi…
RoCoIns: Enhancing Robustness of Large Language Models through Code-Style Instructions
Yuansen Zhang, Xiao Wang, Zhiheng Xi +4
Large Language Models (LLMs) have showcased remarkable capabilities in following human instructions. However, recent studies have raised concerns about the robustness of LLMs when…
GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick
Jiayi Fu, Xuandong Zhao, Ruihan Yang +3
Large language models (LLMs) excellently generate human-like text, but also raise concerns about misuse in fake news and academic dishonesty. Decoding-based watermark, particularly…
TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models
Xiao Wang, Yuansen Zhang, Tianze Chen +9
Aligned large language models (LLMs) demonstrate exceptional capabilities in task-solving, following instructions, and ensuring safety. However, the continual learning aspect of th…
InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction
Xiao Wang, Weikang Zhou, Can Zu +11
Large language models have unlocked strong multi-task capabilities from reading instructive prompts. However, recent studies have shown that existing large models still have diffic…