[HTML][HTML] Opinion Paper:“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for …
Transformative artificially intelligent tools, such as ChatGPT, designed to generate
sophisticated text indistinguishable from that produced by a human, are applicable across a …
sophisticated text indistinguishable from that produced by a human, are applicable across a …
Opinion Paper:“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research …
Transformative artificially intelligent tools, such as ChatGPT, designed to generate
sophisticated text indistinguishable from that produced by a human, are applicable across a …
sophisticated text indistinguishable from that produced by a human, are applicable across a …
Inceptiontime: Finding alexnet for time series classification
This paper brings deep learning at the forefront of research into time series classification
(TSC). TSC is the area of machine learning tasked with the categorization (or labelling) of …
(TSC). TSC is the area of machine learning tasked with the categorization (or labelling) of …
Unravelling the impact of generative artificial intelligence (GAI) in industrial applications: A review of scientific and grey literature
The scope of application of generative artificial intelligence (GAI) in industrial functions is
gaining high prominence in academic and industrial discourses. In this article, we explore …
gaining high prominence in academic and industrial discourses. In this article, we explore …
Interpreting graph neural networks for NLP with differentiable edge masking
Graph neural networks (GNNs) have become a popular approach to integrating structural
inductive biases into NLP models. However, there has been little work on interpreting them …
inductive biases into NLP models. However, there has been little work on interpreting them …
On interpretability of artificial neural networks: A survey
Deep learning as performed by artificial deep neural networks (DNNs) has achieved great
successes recently in many important areas that deal with text, images, videos, graphs, and …
successes recently in many important areas that deal with text, images, videos, graphs, and …
A diagnostic study of explainability techniques for text classification
P Atanasova - Accountable and Explainable Methods for Complex …, 2024 - Springer
Recent developments in machine learning have introduced models that approach human
performance at the cost of increased architectural complexity. Efforts to make the rationales …
performance at the cost of increased architectural complexity. Efforts to make the rationales …
Information bottleneck-based interpretable multitask network for breast cancer classification and segmentation
Breast cancer is one of the most common causes of death among women worldwide. Early
signs of breast cancer can be an abnormality depicted on breast images (eg, mammography …
signs of breast cancer can be an abnormality depicted on breast images (eg, mammography …
Explaining deepfake detection by analysing image matching
This paper aims to interpret how deepfake detection models learn artifact features of images
when just supervised by binary labels. To this end, three hypotheses from the perspective of …
when just supervised by binary labels. To this end, three hypotheses from the perspective of …
A survey on deep hashing methods
Nearest neighbor search aims at obtaining the samples in the database with the smallest
distances from them to the queries, which is a basic task in a range of fields, including …
distances from them to the queries, which is a basic task in a range of fields, including …