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As of February 2026, the global technology landscape is undergoing a significant transformation driven by the increasing regulation of Artificial Intelligence (AI). Governments and regulatory bodies around the world are …
arXiv:2602.21227v1 Announce Type: cross Abstract: As large language models (LLMs) evolve into autonomous agents that execute long-horizon workflows, invoking a …
Caiqi Zhang, Menglin Xia, Xuchao Zhang, Daniel Madrigal, Ankur Mallick, Samuel Kessler, Victor Ruehle, Saravan Rajmohan
arXiv:2602.21228v1 Announce Type: cross Abstract: As applications of large language models (LLMs) become increasingly complex, the demand for robust complex …
Yuancheng Yang, Lin Yang, Xu Wang, Chao Tong, Haihua Yang
arXiv:2602.21233v1 Announce Type: cross Abstract: This technical report introduces AngelSlim, a comprehensive and versatile toolkit for large model compression developed …
Rui Cen, QiangQiang Hu, Hong Huang, Hong Liu, Song Liu, Xin Luo, Lin Niu, Yifan Tan, Decheng Wu, Linchuan Xie, Rubing Yang, Guanghua Yu, Jianchen Zhu
arXiv:2602.21251v1 Announce Type: cross Abstract: Legacy JavaScript systems lack type safety, making maintenance risky. While TypeScript can help, manually adding …
arXiv:2602.21255v1 Announce Type: cross Abstract: We establish a general equilibrium theory for systems of large language model (LLM) agents operating …
arXiv:2602.21267v1 Announce Type: cross Abstract: Cybersecurity threats are becoming increasingly sophisticated, making traditional defense mechanisms and manual red teaming approaches …
arXiv:2602.21269v1 Announce Type: cross Abstract: We present Group Orthogonalized Policy Optimization (GOPO), a new alignment algorithm for large language models …
