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20232026
most citedG-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering

22 citations · 30 across the 34 of their papers we have counts for

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9 papers · 1 filter

cs.CR2026

A Self-Evolving Multi-Agent Framework Defense against LLM Jailbreak Attacks

Tongyan Hu, Bryan Hooi

Large language models (LLMs) remain vulnerable to jailbreak attacks that exploit techniques such as role-playing, obfuscation, code transformation, and multi-step indirection to el…

cs.CR2026

AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing

Yuexin Li, Wenjie Qu, Linyu Wu +5

Existing sentence-level watermarking methods enhance robustness to paraphrasing by anchoring watermarks in sentence semantics. However, their prefix-based designs remain vulnerable…

cs.CR2026

WARD: Adversarially Robust Defense of Web Agents Against Prompt Injections

Tri Cao, Yulin Chen, Hieu Cao +8

Web agents can autonomously complete online tasks by interacting with websites, but their exposure to open web environments makes them vulnerable to prompt injection attacks embedd…

cs.CR2026

WebAgentGuard: A Reasoning-Driven Guard Model for Detecting Prompt Injection Attacks in Web Agents

Yulin Chen, Tri Cao, Haoran Li +7

Web agents powered by vision-language models (VLMs) enable autonomous interaction with web environments by perceiving and acting on both visual and textual webpage content to accom…

cs.CR2026

Zombie Agents: Persistent Control of Self-Evolving LLM Agents via Self-Reinforcing Injections

Xianglin Yang, Yufei He, Shuo Ji +2

Self-evolving LLM agents update their internal state across sessions, often by writing and reusing long-term memory. This design improves performance on long-horizon tasks but crea…

cs.CR2025

Backdoor-Powered Prompt Injection Attacks Nullify Defense Methods

Yulin Chen, Haoran Li, Yuan Sui +2

With the development of technology, large language models (LLMs) have dominated the downstream natural language processing (NLP) tasks. However, because of the LLMs' instruction-fo…