Machine-generated text: A comprehensive survey of threat models and detection methods

EN Crothers, N Japkowicz, HL Viktor - IEEE Access, 2023 - ieeexplore.ieee.org
Machine-generated text is increasingly difficult to distinguish from text authored by humans.
Powerful open-source models are freely available, and user-friendly tools that democratize …

Large language models for forecasting and anomaly detection: A systematic literature review

J Su, C Jiang, X Jin, Y Qiao, T Xiao, H Ma… - arXiv preprint arXiv …, 2024 - arxiv.org
This systematic literature review comprehensively examines the application of Large
Language Models (LLMs) in forecasting and anomaly detection, highlighting the current …

Chatgpt perpetuates gender bias in machine translation and ignores non-gendered pronouns: Findings across bengali and five other low-resource languages

S Ghosh, A Caliskan - Proceedings of the 2023 AAAI/ACM Conference …, 2023 - dl.acm.org
In this multicultural age, language translation is one of the most performed tasks, and it is
becoming increasingly AI-moderated and automated. As a novel AI system, ChatGPT claims …

Language modeling is compression

G Delétang, A Ruoss, PA Duquenne, E Catt… - arXiv preprint arXiv …, 2023 - arxiv.org
It has long been established that predictive models can be transformed into lossless
compressors and vice versa. Incidentally, in recent years, the machine learning community …

Design of a modified transformer architecture based on relative position coding

W Zheng, G Gong, J Tian, S Lu, R Wang, Z Yin… - International Journal of …, 2023 - Springer
Natural language processing (NLP) based on deep learning provides a positive
performance for generative dialogue system, and the transformer model is a new boost in …

[图书][B] Neural networks and deep learning

CC Aggarwal - 2018 - Springer
“Any AI smart enough to pass a Turing test is smart enough to know to fail it.”–*** Ian
McDonald Neural networks were developed to simulate the human nervous system for …

[图书][B] Neural network methods in natural language processing

Y Goldberg - 2017 - books.google.com
Neural networks are a family of powerful machine learning models and this book focuses on
their application to natural language data. The first half of the book (Parts I and II) covers the …

[PDF][PDF] Performance evaluation of deep neural networks applied to speech recognition: RNN, LSTM and GRU

A Shewalkar, D Nyavanandi, SA Ludwig - Journal of Artificial …, 2019 - sciendo.com
Abstract Deep Neural Networks (DNN) are nothing but neural networks with many hidden
layers. DNNs are becoming popular in automatic speech recognition tasks which combines …

Debiasing scores and prompts of 2d diffusion for view-consistent text-to-3d generation

S Hong, D Ahn, S Kim - Advances in Neural Information …, 2023 - proceedings.neurips.cc
Existing score-distilling text-to-3D generation techniques, despite their considerable
promise, often encounter the view inconsistency problem. One of the most notable issues is …

Ordered neurons: Integrating tree structures into recurrent neural networks

Y Shen, S Tan, A Sordoni, A Courville - arXiv preprint arXiv:1810.09536, 2018 - arxiv.org
Natural language is hierarchically structured: smaller units (eg, phrases) are nested within
larger units (eg, clauses). When a larger constituent ends, all of the smaller constituents that …