arXiv:2511. 13480v2 Announce Type: replace-cross Abstract: This study focuses on understanding the complex dynamics between humans and AI systems by analyzing user reviews.
By Parisa Arbab, Xiaowen Fang
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
AI-assisted peer review is increasingly discussed and adopted as a tool to support the scientific publishing process, yet there is little systematic understanding of how publication venues regulate its use or of how capable current AI review systems are. We address these questions by first surveying reviewer-facing AI policies across 111 leading AI/NLP conferences and medical journals, revealing substantial regulation differences between the two communities.
arXiv:2608. 03581v1 Announce Type: cross Abstract: AI-assisted peer review is increasingly discussed and adopted as a tool to support the scientific publishing process, yet there is little systematic understanding of how publication venues regulate its use or of how capable current AI review systems are.
By Alexander M. Fichtl, Lukas Ellinger, Josefin Kelber, Kry\v{s}tof Ol\'ik, Georg Groh
arXiv:2607. 01387v1 Announce Type: cross Abstract: Recommender systems are vital in helping users navigate vast amounts of information, offering personalized suggestions and effective explanations for these recommendations.
By Longfeng Wu, Yao Zhou, Tong Zeng, Zhimin Peng, Bhanu Pratap Singh Rawat, Lecheng Zheng, Giovanni Seni, Dawei Zhou
Recommender systems are vital in helping users navigate vast amounts of information, offering personalized suggestions and effective explanations for these recommendations. While previous efforts have attempted to provide such explanations, evaluating their effectiveness across various scenarios remains a challenge.