7 papers
Transferable End-to-End Optimization for Indirect Long-Term Memory Poisoning in LLM Agents
Chuanchao Zang, Jianing Wang, Wenyu Chen +5
Long-term memory can turn untrusted external content into persistent influence over an LLM agent's future decisions, creating the threat of indirect memory poisoning. A successful…
Extracting Knowledge from Tools in LLM Agents
Chuanchao Zang, Jianing Wang, Wenyu Chen +6
LLM agents commonly use knowledge-based tools and access their underlying files, databases, and search indexes through tool invocation. This integration improves agents' ability to…
Understanding Stage-Wise Utility-Risk Trade-offs in LLM Agent Memory
Chuanchao Zang, Zijian Cao, Xiangtao Meng +6
Long-term memory is becoming a core capability of LLM agents, enabling personalization and long-horizon interaction. However, memory mechanisms that retain, transform, or expose mo…
Isolated but Exposed: Persistence-Based Memory Extraction Attack on LLM Agents
Xinyu Gao, Wenyu Chen, Xiangtao Meng +5
LLM-based agents extend large language models with long-term memory (LTM) that persists privacy-sensitive user data across sessions. Production systems mitigate extraction risks th…
Hidden Decoding at Scale: Latent Computation Scaling for Large Language Models
Aiwei Liu, Cheng Shi, Chuhan Wu +44
Scaling Large Language Models (LLMs) has been driven mainly by enlarging the Transformer backbone, but for an already-strong model this requires another round of costly pretraining…
Not All Tokens Are Created Equal: Query-Efficient Jailbreak Fuzzing for LLMs
Wenyu Chen, Xiangtao Meng, Chuanchao Zang +6
Large Language Models(LLMs) are widely deployed, yet are vulnerable to jailbreak prompts that elicit policy-violating outputs. Although prior studies have uncovered these risks, th…