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20232026
most citedBenchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach

4 citations · 6 across the 16 of their papers we have counts for

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7 papers · 1 filter

cs.CR2026

Reassembling Distributed Risk: Trajectory-Conditioned Action Generation for Multi-Turn Agent Safety

Yanbo Dai, Zhenlan Ji, Zongjie Li +1

Tool-using LLM agents extend security risks beyond generated text to actions that affect external systems. Under multi-turn decomposition attacks, a harmful objective can be distri…

cs.CR2026

Detecting and Understanding Vulnerabilities in Fully Homomorphic Encryption Frameworks

Yiteng Peng, Dongwei Xiao, Zhibo Liu +2

Fully homomorphic encryption (FHE) allows computations to be performed directly on encrypted data without decryption, offering strong privacy guarantees for sensitive data analysis…

cs.CR2025

SEAL: Subspace-Anchored Watermarks for LLM Ownership

Yanbo Dai, Zongjie Li, Zhenlan Ji +1

Large language models (LLMs) have achieved remarkable success across a wide range of natural language processing tasks, demonstrating human-level performance in text generation, re…

cs.CR2025

DisarmRAG: Stealthy Retriever-Centric Poisoning to Disable Self-Correction in Retrieval-Augmented Generation (Extended Version)

Yanbo Dai, Zhenlan Ji, Zongjie Li +2

Retrieval-Augmented Generation (RAG) has become a standard approach for improving the reliability of large language models (LLMs). Prior work demonstrates the vulnerability of RAG…

cs.CR2025

IP Leakage Attacks Targeting LLM-Based Multi-Agent Systems

Liwen Wang, Wenxuan Wang, Shuai Wang +5

The rapid advancement of Large Language Models (LLMs) has led to the emergence of Multi-Agent Systems (MAS) to perform complex tasks through collaboration. However, the intricate n…

cs.CR2025

SoK: Evaluating Jailbreak Guardrails for Large Language Models

Xunguang Wang, Zhenlan Ji, Wenxuan Wang +3

Large Language Models (LLMs) have achieved remarkable progress, but their deployment has exposed critical vulnerabilities, particularly to jailbreak attacks that circumvent safety…