A survey of controllable text generation using transformer-based pre-trained language models
Controllable Text Generation (CTG) is an emerging area in the field of natural language
generation (NLG). It is regarded as crucial for the development of advanced text generation …
generation (NLG). It is regarded as crucial for the development of advanced text generation …
A bibliometric review of large language models research from 2017 to 2023
Large language models (LLMs), such as OpenAI's Generative Pre-trained Transformer
(GPT), are a class of language models that have demonstrated outstanding performance …
(GPT), are a class of language models that have demonstrated outstanding performance …
From pretraining data to language models to downstream tasks: Tracking the trails of political biases leading to unfair NLP models
Language models (LMs) are pretrained on diverse data sources, including news, discussion
forums, books, and online encyclopedias. A significant portion of this data includes opinions …
forums, books, and online encyclopedias. A significant portion of this data includes opinions …
Sora: A review on background, technology, limitations, and opportunities of large vision models
Sora is a text-to-video generative AI model, released by OpenAI in February 2024. The
model is trained to generate videos of realistic or imaginative scenes from text instructions …
model is trained to generate videos of realistic or imaginative scenes from text instructions …
A review on large Language Models: Architectures, applications, taxonomies, open issues and challenges
Large Language Models (LLMs) recently demonstrated extraordinary capability in various
natural language processing (NLP) tasks including language translation, text generation …
natural language processing (NLP) tasks including language translation, text generation …
ROBBIE: Robust bias evaluation of large generative language models
As generative large language models (LLMs) grow more performant and prevalent, we must
develop comprehensive enough tools to measure and improve their fairness. Different …
develop comprehensive enough tools to measure and improve their fairness. Different …
The moral integrity corpus: A benchmark for ethical dialogue systems
Conversational agents have come increasingly closer to human competence in open-
domain dialogue settings; however, such models can reflect insensitive, hurtful, or entirely …
domain dialogue settings; however, such models can reflect insensitive, hurtful, or entirely …
Fairness in deep learning: A survey on vision and language research
Despite being responsible for state-of-the-art results in several computer vision and natural
language processing tasks, neural networks have faced harsh criticism due to some of their …
language processing tasks, neural networks have faced harsh criticism due to some of their …
Language generation models can cause harm: So what can we do about it? an actionable survey
Recent advances in the capacity of large language models to generate human-like text have
resulted in their increased adoption in user-facing settings. In parallel, these improvements …
resulted in their increased adoption in user-facing settings. In parallel, these improvements …
Efficient utilization of pre-trained models: A review of sentiment analysis via prompt learning
K Bu, Y Liu, X Ju - Knowledge-Based Systems, 2024 - Elsevier
Sentiment analysis is one of the traditional well-known tasks in Natural Language
Processing (NLP) research. In recent years, Pre-trained Models (PMs) have become one of …
Processing (NLP) research. In recent years, Pre-trained Models (PMs) have become one of …