The threat of cryptographically relevant quantum computers, compounded by harvest now, decrypt later attacks, has made migration to post-quantum cryptography (PQC) urgent. With PQC standards finalized and transition guidance phasing out quantum-vulnerable algorithms, the readiness of the open-source supply chain, throu...
Tong-Xin Yuan, Zhan-Peng Liu, Jia-Shuo Liang et al.· Proceedings of the 41st IEEE...· 0 citations
The Evidence-Grounded, Social-Weighted Persona Panel is proposed, a three-stage GenUI evaluation method in which a panel of psychologically diverse, evidence-grounded personas independently rates a screenshot, exchanges opinions under a trait-derived, semantically-gated bounded-confidence mechanism, and is aggregated v...
Zheng Wu, Yibo Luo, Pu Zhang et al.· arXiv.org· 0 citations
An entropy-based poisoning filter that mitigates task-agnostic backdoor attacks due to vulnerabilities in data and training mechanisms and injects multiple syntactic backdoors into the pre-training space through corpus poisoning, while preserving the PLM's pre-training capabilities.
Pengzhou Cheng, Wei Du, Zongru Wu et al.· North American Chapter of th...· 9 citations· ⚡3
MineExplorer benchmark for evaluating open-world exploration capabilities of MLLM agents in Minecraft is introduced, which first filter atomic tasks whose solutions rely heavily on Minecraft-specific knowledge to better reflect general open-world reasoning and compose atomic tasks into implicit multi-hop tasks.
Results validate that a lightweight inference-time intervention can substantially boost GUI Agent's competence to identify inappropriate execution scenarios and refrain from unnecessary actions.
Zhao-Yuan Huang, Tian-Jie Ju, Pengzhou Cheng et al.· 1 citation
Persuasion Duality is identified: reasoning enhances an agent's persuasive power while simultaneously increasing its resistance to persuasion, and a prompt-level adversarial argument detection method is proposed that consistently improves agent robustness.
This paper proposes UrbanGround, the first sandbox to make this question testable in a physically constrained replica of Hong Kong built from territory-wide 3D geospatial data, and hopes it will support broader study of how far current MLLM agents can explore reliably in complex, open-ended urban environments.
Tianjie Ju, Zheng Wu, Yue-Qing Sun et al.· 2 citations
The findings relocate the bottleneck of commonsense reasoning failures from model competence to elicitation, and release SaliTrap as a testbed for this blind spot, to show that lightweight, inference-time prompting alone substantially closes the gap without any retraining.
