collaborators

9 papers

cs.CR2026

SoK: Intent-Oriented Systematization of Multi-Turn LLM Jailbreaks

Siyuan Li, Aodu Wulianghai, Zehao Liu +8

Large Language Models (LLMs) are increasingly deployed in interactive settings, where user intent commonly unfolds through multi-turn dialogue. Multi-turn jailbreaks exploit this p…

cs.CR2026

Stateful Cooperative Agents Safeguarding LLMs Against Evolving Multi-Turn Attacks

Siyuan Li, Zehao Liu, Haoyu Li +5

As LLMs become increasingly integrated into complex applications, their vulnerability to adversarial attacks has raised significant concerns. However, existing defenses remain reac…

cs.CL2026

Lightweight Stylistic Consistency Profiling: Robust Detection of LLM-Generated Textual Content for Multimedia Moderation

Siyuan Li, Aodu Wulianghai, Xi Lin +6

The increasing prevalence of Large Language Models (LLMs) in content creation has made distinguishing human-written textual content from LLM-generated counterparts a critical task…

cs.CL2026

DSIPA: Detecting LLM-Generated Texts via Sentiment-Invariant Patterns Divergence Analysis

Siyuan Li, Aodu Wulianghai, Guangyan Li +5

The rapid advancement of large language models (LLMs) presents new security challenges, particularly in detecting machine-generated text used for misinformation, impersonation, and…

cs.CR2026

CoopGuard: Stateful Cooperative Agents Safeguarding LLMs Against Evolving Multi-Round Attacks

Siyuan Li, Zehao Liu, Xi Lin +6

As Large Language Models (LLMs) are increasingly deployed in complex applications, their vulnerability to adversarial attacks raises urgent safety concerns, especially those evolvi…

cs.CR2026

HoneyTrap: Deceiving Large Language Model Attackers to Honeypot Traps with Resilient Multi-Agent Defense

Siyuan Li, Xi Lin, Jun Wu +5

Jailbreak attacks pose significant threats to large language models (LLMs), enabling attackers to bypass safeguards. However, existing reactive defense approaches struggle to keep…