Results 11 to 20 of about 15,304,814 (364)
Survey of Hallucination in Natural Language Generation [PDF]
ACM Computing Surveys, 2022 Natural Language Generation (NLG) has improved exponentially in recent years thanks to the development of sequence-to-sequence deep learning technologies such as Transformer-based language models. This advancement has led to more fluent and coherent NLG,
Ziwei Ji +11 more
semanticscholar +1 more source
Knowledge Distillation: A Survey [PDF]
International Journal of Computer Vision, 2020 In recent years, deep neural networks have been successful in both industry and academia, especially for computer vision tasks. The great success of deep learning is mainly due to its scalability to encode large-scale data and to maneuver billions of ...
Jianping Gou, B. Yu, S. Maybank, D. Tao
semanticscholar +1 more source
A Survey on Evaluation of Large Language Models [PDF]
ACM Transactions on Intelligent Systems and Technology, 2023 Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, their evaluation becomes
Yu-Chu Chang +15 more
semanticscholar +1 more source
A survey on large language model based autonomous agents [PDF]
Frontiers of Computer Science, 2023 Autonomous agents have long been a research focus in academic and industry communities. Previous research often focuses on training agents with limited knowledge within isolated environments, which diverges significantly from human learning processes ...
Lei Wang +12 more
semanticscholar +1 more source
A Survey on Bias and Fairness in Machine Learning [PDF]
ACM Computing Surveys, 2019 With the widespread use of artificial intelligence (AI) systems and applications in our everyday lives, accounting for fairness has gained significant importance in designing and engineering of such systems.
Ninareh Mehrabi +4 more
semanticscholar +1 more source
A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2020 A convolutional neural network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limited to computer vision and natural language processing, it attracted much
Zewen Li +4 more
semanticscholar +1 more source
Transformers in Vision: A Survey [PDF]
ACM Computing Surveys, 2021 Astounding results from Transformer models on natural language tasks have intrigued the vision community to study their application to computer vision problems.
Salman Hameed Khan +5 more
semanticscholar +1 more source
Diffusion Models: A Comprehensive Survey of Methods and Applications [PDF]
ACM Computing Surveys, 2022 Diffusion models have emerged as a powerful new family of deep generative models with record-breaking performance in many applications, including image synthesis, video generation, and molecule design.
Ling Yang +8 more
semanticscholar +1 more source
A Survey of Methods for Explaining Black Box Models [PDF]
ACM Computing Surveys, 2018 In recent years, many accurate decision support systems have been constructed as black boxes, that is as systems that hide their internal logic to the user. This lack of explanation constitutes both a practical and an ethical issue.
Riccardo Guidotti +4 more
semanticscholar +1 more source
A survey on deep learning in medical image analysis [PDF]
Medical Image Anal., 2017 Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 ...
G. Litjens +8 more
semanticscholar +1 more source