Agents are increasingly susceptible to hijack attacks, where malicious instructions embedded in cross-modal inputs (e.g., adversarial images or retrieved web content) are used to deceive the agent's execution. Existing defenses typically rely on strict filtering or refusal mechanisms, which suffer from a critical limit...
Che Wang, Fu-Yao Zhang, Jiaming Zhang et al.· 0 citations
A novel Continual Learning Dynamic Graph LLM framework (Continual-GraphLLM) is proposed to continually adapt to incoming patterns by routing them to experts specialized in similar past patterns, while mitigating the overwriting of previously learned patterns by assigning new experts to unseen patterns.
Tianhang Wan, Xin Wang, Haibo Chen et al.· Proceedings of the 32nd ACM...· 0 citations
Dynamic text-attributed graphs (DyTAGs) exhibit coupled textual and structural dynamics, and existing mainstream approaches for DyTAGs extend conventional large language models (LLMs) to capture both dynamics, thereby giving rise to dynamic graph LLMs. However, in DyTAGs, the continuous emergence of new nodes and edges...
Tianhang Wan, Xin Wang, Haibo Chen et al.· Proceedings of the 32nd ACM...· 0 citations
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