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20242026
most citedTrustworthy AI-Generative Content for Intelligent Network Service: Robustness, Security, and Fairness

2 citations · 3 across the 12 of their papers we have counts for

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Showing cs.CRShow all

5 papers · 1 filter

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.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…

cs.CR2024★ 2 cited

Trustworthy AI-Generative Content for Intelligent Network Service: Robustness, Security, and Fairness

Siyuan Li, Xi Lin, Yaju Liu +2

AI-generated content (AIGC) models, represented by large language models (LLM), have revolutionized content creation. High-speed next-generation communication technology is an idea…