Copertina

Generative AI in the Construction Industry: Opportunities & Challenges

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ghimire, Prashnna, Kim, Kyungki, Acharya, Manoj
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

On the Challenges and Opportunities in Generative AI
di: Manduchi, Laura, et al.
Pubblicazione: (2024)

Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges
di: Reddy, Chandan K, et al.
Pubblicazione: (2024)

Generative AI for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations
di: Fleurence, Rachael, et al.
Pubblicazione: (2024)

Reinforcement Learning for Generative AI: State of the Art, Opportunities and Open Research Challenges
di: Franceschelli, Giorgio, et al.
Pubblicazione: (2023)

FinXplore: An Adaptive Deep Reinforcement Learning Framework for Balancing and Discovering Investment Opportunities
di: Choudhary, Himanshu, et al.
Pubblicazione: (2025)

Continual Learning on Graphs: Challenges, Solutions, and Opportunities
di: Zhang, Xikun, et al.
Pubblicazione: (2024)

On-board Telemetry Monitoring in Autonomous Satellites: Challenges and Opportunities
di: Capelli, Lorenzo, et al.
Pubblicazione: (2026)

Generative AI in the Construction Industry: A State-of-the-art Analysis
di: Taiwo, Ridwan, et al.
Pubblicazione: (2024)

Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities
di: He, Wenchong, et al.
Pubblicazione: (2023)

Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities
di: Hao, Zhiwei, et al.
Pubblicazione: (2025)

From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare
di: Li, Ming, et al.
Pubblicazione: (2024)

Compare different SG-Schemes based on large least square problems
di: Acharya, Ramkrishna
Pubblicazione: (2025)

Supervised Pretraining for Material Property Prediction
di: Rahman, Chowdhury Mohammad Abid, et al.
Pubblicazione: (2025)

Challenges and Limitations of Generative AI in Synthesizing Wearable Sensor Data
di: Di Martino, Flavio, et al.
Pubblicazione: (2025)

The Age of Synthetic Realities: Challenges and Opportunities
di: Cardenuto, João Phillipe, et al.
Pubblicazione: (2023)

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription
di: Alkaeed, Mahdi, et al.
Pubblicazione: (2025)

Neurosymbolic AI for Travel Demand Prediction: Integrating Decision Tree Rules into Neural Networks
di: Acharya, Kamal, et al.
Pubblicazione: (2025)

AssurAI: Experience with Constructing Korean Socio-cultural Datasets to Discover Potential Risks of Generative AI
di: Lim, Chae-Gyun, et al.
Pubblicazione: (2025)

Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities
di: Lin, Zheng, et al.
Pubblicazione: (2023)

Towards Fully Automated Decision-Making Systems for Greenhouse Control: Challenges and Opportunities
di: Liu, Yongshuai, et al.
Pubblicazione: (2025)

Enhancing material property prediction with ensemble deep graph convolutional networks
di: Rahman, Chowdhury Mohammad Abid, et al.
Pubblicazione: (2024)

Data-Driven Methods and AI in Engineering Design: A Systematic Literature Review Focusing on Challenges and Opportunities
di: Afifi, Nehal, et al.
Pubblicazione: (2025)

Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference
di: Samplawski, Colin, et al.
Pubblicazione: (2025)

Foundation Models for CPS-IoT: Opportunities and Challenges
di: Baris, Ozan, et al.
Pubblicazione: (2025)

ML For Hardware Design Interpretability: Challenges and Opportunities
di: Baartmans, Raymond, et al.
Pubblicazione: (2025)

Multimodal Federated Learning in Healthcare: a Review
di: Thrasher, Jacob, et al.
Pubblicazione: (2023)

Construction of Knowledge Graphs: State and Challenges
di: Hofer, Marvin, et al.
Pubblicazione: (2023)

Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety
di: Korbak, Tomek, et al.
Pubblicazione: (2025)

Opportunities and Challenges of Frontier Data Governance With Synthetic Data
di: Thakur, Madhavendra, et al.
Pubblicazione: (2025)

AI in Manufacturing: Market Analysis and Opportunities
di: Abdelaal, Mohamed
Pubblicazione: (2024)

Grokking as a Variance-Limited Phase Transition: Spectral Gating and the Epsilon-Stability Threshold
di: Acharya, Pratyush, et al.
Pubblicazione: (2026)

Activation Sparsity Opportunities for Compressing General Large Language Models
di: Dhar, Nobel, et al.
Pubblicazione: (2024)

Analysis of the Memorization and Generalization Capabilities of AI Agents: Are Continual Learners Robust?
di: Kim, Minsu, et al.
Pubblicazione: (2023)

Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text
di: Abdali, Sara, et al.
Pubblicazione: (2024)

The Hardness of Achieving Impact in AI for Social Impact Research: A Ground-Level View of Challenges & Opportunities
di: Majumdar, Aditya, et al.
Pubblicazione: (2025)

Position: Challenges and Opportunities for Differential Privacy in the U.S. Federal Government
di: Khanna, Amol, et al.
Pubblicazione: (2024)

Investigating Trustworthiness of Nonparametric Deep Survival Models for Alzheimer's Disease Progression Analysis
di: Thrasher, Jacob, et al.
Pubblicazione: (2026)

Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges
di: Ibrahim, Mahmoud, et al.
Pubblicazione: (2024)

Characterization of Multi-Model Agentic AI Systems on General Tasks via Trace-Driven Simulation
di: Kim, Donghwan, et al.
Pubblicazione: (2026)

Neuro-Symbolic AI: Explainability, Challenges, and Future Trends
di: Zhang, Xin, et al.
Pubblicazione: (2024)