arXiv:2606. 02184v1 Announce Type: cross Abstract: These names do not exist.
By Micha{\l} Brzozowski, Neo Christopher Chung
arXiv:2608. 05157v1 Announce Type: cross Abstract: Double blind peer review serves as the scientific community primary defense against status and affiliation bias.
By Bulambo Mwendelwa Gloire, Prasenjit Mitra
arXiv:2606. 11105v1 Announce Type: cross Abstract: Hallucinations, where language models (LMs) generate factually ungrounded responses, pose serious risks, as users tend to blindly rely on them.
By Haeji Jung, Hila Gonen
arXiv:2606. 10794v1 Announce Type: new Abstract: As agentic applications increasingly route user tasks through official and third-party LLM APIs, provenance becomes an operational question: which model generated a given black-box response?
By Jiaxu Liu, Sunnan Mu, Dong Huang, Liuyin Wang, Jing Shao, Jie Zhang
arXiv:2606. 18060v1 Announce Type: new Abstract: As Large Language Model based agents enter autonomous scientific research, their ability to resist pseudoscience becomes increasingly important.
By Xinyang Liao, Lingyu Li, Huacan Liu, Tianle Gu, Yang Yao, Tong Zhu, Yan Teng, Yingchun Wang
arXiv:2607. 00738v1 Announce Type: cross Abstract: Large language models can generate polished scientific text that includes unsupported claims, allowing hallucinations to enter the archival record.
By Mark Russinovich, Ram Shankar Siva Kumar, Ahmed Salem