Results 11 to 20 of about 8,553,581 (297)
A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions [PDF]
ACM Trans. Inf. Syst., 2023 The emergence of large language models (LLMs) has marked a significant breakthrough in natural language processing (NLP), fueling a paradigm shift in information acquisition.
Lei Huang +10 more
semanticscholar +1 more source
ChatGPT for good? On opportunities and challenges of large language models for education
Learning and Individual Differences, 2023 Large language models represent a significant advancement in the field of AI. The underlying technology is key to further innovations and, despite critical views and even bans within communities and regions, large language models are here to stay.
Enkelejda Kasneci +22 more
semanticscholar +1 more source
Facilitating Constructive Discussions of Difficult Socio-Scientific Issues
Journal of Microbiology & Biology Education, 2021 Discussion can be an important and powerful tool in efforts to build a more diverse, equitable, and inclusive future for STEM (i.e., science, technology, engineering, and mathematics).
Gregory R. Goldsmith +9 more
doaj +1 more source
Acknowledgment to the Reviewers of Challenges in 2022
Challenges, 2023 High-quality academic publishing is built on rigorous peer review [...]
Challenges Editorial Office
doaj +1 more source
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Journal of Big Data, 2021 In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving ...
Laith Alzubaidi +9 more
semanticscholar +1 more source
Federated Learning: Challenges, Methods, and Future Directions [PDF]
IEEE Signal Processing Magazine, 2019 Federated learning involves training statistical models over remote devices or siloed data centers, such as mobile phones or hospitals, while keeping data localized.
Tian Li +3 more
semanticscholar +1 more source
Acknowledgment of Reviewers of Challenges in 2020
Challenges, 2021 Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Challenges maintains its standards for the high quality of its published papers [...]
Challenges Editorial Office
doaj +1 more source
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges [PDF]
Information Fusion, 2020 Uncertainty quantification (UQ) plays a pivotal role in reduction of uncertainties during both optimization and decision making processes. It can be applied to solve a variety of real-world applications in science and engineering.
M. Abdar +11 more
semanticscholar +1 more source
Acknowledgment to Reviewers of Challenges in 2021
Challenges, 2022 Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Challenges Editorial Office
doaj +1 more source