arXiv:2607. 29343v1 Announce Type: new Abstract: Artificial intelligence is increasingly embedded in everyday software, making its integration into mobile apps inevitable.
By Babar Shah, Faheem Ullah, Myles Watkinson, Muhammad Moiz Khalid, Tehmina Karamat Khan, Muhammad Junaid
arXiv:2606. 16072v1 Announce Type: cross Abstract: Compared with binaries and decompiled code, malware source code more directly reflects the attackers' original intent.
By Bojing Li, Duo Zhong, Prajna Bhandary, Raguvir S, Charles Maxa, Robert J Joyce, Charles Nicholas
arXiv:2608. 10970v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have demonstrated strong capabilities in generating semantically relevant concepts and relations, making them promising tools for taxonomy enrichment.
By Zeinab Ghamlouch, Mehwish Alam
Recent advances in Large Language Models (LLMs) have demonstrated strong capabilities in generating semantically relevant concepts and relations, making them promising tools for taxonomy enrichment. However, directly relying on LLM-generated expansions often leads to noisy, redundant, or hierarchically inconsistent structures, limiting their reliability for automated taxonomy expansion.
arXiv:2607. 22695v1 Announce Type: new Abstract: Large Language Models (LLMs) are capable of generalizing human language for the completion of never-before-seen tasks, leading to widespread deployment.
By Ryan Thornton, Mir Mehedi Ahsan Pritom, Maanak Gupta
arXiv:2512. 10234v2 Announce Type: replace-cross Abstract: Even LLMs that appear safe during evaluation can still produce harmful responses in deployment.
By Junhyeong Hwangbo, Soohyun Lee, Hyeon Jeon, Kyochul Jang, Minsoo Cheong, Youngjae Yu, Jinwook Seo