A systematic literature review on text generation using deep neural network models
In recent years, significant progress has been made in text generation. The latest text
generation models are revolutionizing the domain by generating human-like text. It has …
generation models are revolutionizing the domain by generating human-like text. It has …
Recent advances in neural text generation: A task-agnostic survey
In recent years, considerable research has been dedicated to the application of neural
models in the field of natural language generation (NLG). The primary objective is to …
models in the field of natural language generation (NLG). The primary objective is to …
Neural natural language generation: A survey on multilinguality, multimodality, controllability and learning
Developing artificial learning systems that can understand and generate natural language
has been one of the long-standing goals of artificial intelligence. Recent decades have …
has been one of the long-standing goals of artificial intelligence. Recent decades have …
Discrete memristive neuron model and its interspike interval-encoded application in image encryption
Bursting is a diverse and common phenomenon in neuronal activation patterns and it
indicates that fast action voltage spiking periods are followed by resting periods. The …
indicates that fast action voltage spiking periods are followed by resting periods. The …
A multi-scenario text generation method based on meta reinforcement learning
Multi-scenario text generation is an essential task in natural language generation because
of the multi-scene interlaced property of real-world problems. Traditional methods typically …
of the multi-scene interlaced property of real-world problems. Traditional methods typically …
Causal reasoning in typical computer vision tasks
Deep learning has revolutionized the field of artificial intelligence. Based on the statistical
correlations uncovered by deep learning-based methods, computer vision tasks, such as …
correlations uncovered by deep learning-based methods, computer vision tasks, such as …
Predictive typing method for Persian office automation
B Nouraei, J Shanbehzadeh, P Asghari - Engineering Applications of …, 2024 - Elsevier
Typing is a time-consuming task and predictive text is proposed as a solution. Recently,
Generative Pre-trained Transformers (GPT) have employed autoregressive deep learning to …
Generative Pre-trained Transformers (GPT) have employed autoregressive deep learning to …
Integrating AI planning with natural language processing: a combination of explicit and tacit knowledge
K Jin, HH Zhuo - arXiv preprint arXiv:2202.07138, 2022 - arxiv.org
Natural language processing (NLP) aims at investigating the interactions between agents
and humans, processing and analyzing large amounts of natural language data. Large …
and humans, processing and analyzing large amounts of natural language data. Large …
Abstractive Text Summarization for Contemporary Sanskrit Prose: Issues and Challenges
S Sinha - arXiv preprint arXiv:2501.01933, 2025 - arxiv.org
This thesis presents Abstractive Text Summarization models for contemporary Sanskrit
prose. The first chapter, titled Introduction, presents the motivation behind this work, the …
prose. The first chapter, titled Introduction, presents the motivation behind this work, the …
An overview of indian language datasets used for text summarization
In this paper, we survey text summarization (TS) datasets in Indian languages (ILs), which
are also low-resource languages (LRLs). We seek to answer one primary question—is the …
are also low-resource languages (LRLs). We seek to answer one primary question—is the …