Dec 2026· Geo Journal of Tourism and Geosites· 0 citations
Abstract
The Tourism 5.0 paradigm is emerging as a pivotal response to the limits of a purely efficiency-oriented digitalisation,
by placing people and sustainability back at the centre of innovation to create a holistic and responsible tourism ecosystem.
Within the framework of Vision 2030, Saudi Arabia has adopted this orientation as a lever for economic diversification as a
leading international tourism destination drawn on its cultural heritage and natural resources. However, the shift from theory to
practice, in a context of very rapid transformation, raises questions about the balance between technological automation and
authentic cultural experience. To address such questions and explore the tension between automation and authenticity resulted
from the transition towards Tourism 5.0, a qualitative interpretive approach was undertaken. Based on 24 in-depth interviews
conducted with Saudi and international experts during the TOURISE 2025 event. The reason for the interviews is to delve
deeply into experts’ perceptions on how artificial intelligence and data are being integrated into the tourism sector as well as
addressing the potential conflict between digitalization and authenticity. The findings reveal a strong ambition to build a
Saudi "smart heritage" for enhancing, not replacing, cultural experience. There is also a need for structural challenges related
to the development of hybrid skills among the workforces. The skills should include mixing technological proficiency with
deep cultural knowledge and hospitality expertise proficiency. The results also emphasised the inclusion of small local
tourism and hospitality businesses for successful transition. Implications of these findings are then discussed and elaborated.
This paper investigates developing real-world perception for active agents, proposes Gibson Environment for this purpose, and showcases a set of perceptual tasks learned therein.
F. Xia, Amir Zamir, Zhi-Yang He et al.· 2018 IEEE/CVF Conference on...· 1,069 citations· ⚡112
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
An algorithm is proposed which leverages disentangled semantic factors to generate adversarial perturbation by altering controlled semantic attributes to fool the learner towards various "adversarial" targets.
Haonan Qiu, Chaowei Xiao, Lei Yang et al.· arXiv.org· 208 citations· ⚡17
This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9