arXiv:2609.05552v1 Announce Type: cross
Abstract: Industrial environments increasingly rely on collaboration between humans and AI-enabled agents. Effective teamwork requires aligning how agents perc...
By Kolitha Kottagaha W. M, Jos A. C. Bokhorst, Ben Gaffinet, Christos Emmanouilidis
arXiv:2607. 21547v1 Announce Type: new Abstract: The rapid progress of AI has intensified the long-standing pursuit of automation: replacing human participation with algorithms wherever possible.
By Fares Fourati, Hinrich Sch\"utze, Eyke H\"ullermeier, Iryna Gurevych
arXiv:2606. 05222v1 Announce Type: cross Abstract: Artificial intelligence (AI) has been applied across educational contexts to support learning.
By Luis P. Prieto, Juan I. Asensio-P\'erez, Mar\'ia Jes\'us Rodr\'iguez-Triana, Mohamed Saban, Yannis Dimitriadis
The paper surveys how Large Foundation Models (LFMs) can be integrated into Human‑AI Collaboration (HAI) to enhance problem‑solving and decision‑making. It outlines four key areas—human‑guided model development, collaborative design principles, ethical and governance frameworks, and high‑stakes applications—while emphasizing that effective HAI systems arise from careful, human‑centered design rather than merely stronger models. The survey also identifies open challenges related to safety, fairness, and control, aiming to guide future research toward reliable, trustworthy, and beneficial LFM‑based partnerships.
By Vanshika Vats, Marzia Binta Nizam, Minghao Liu, Ziyuan Wang, Richard Ho, Mohnish Sai Prasad, Vincent Titterton, Sai Venkat Malreddy, Riya Aggarwal, Yanwen Xu, Lei Ding, Jay Mehta, Nathan Grinnell, Li Liu, Sijia Zhong, Devanathan Nallur Gandamani, Xinyi Tang, Rohan Ghosalkar, Celeste Shen, Rachel Shen, Nafisa Hussain, Kesav Ravichandran, James Davis