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Poetry represents the oldest and most esteemed literary form, allowing poets to convey ideas while carefully attending to elements such as meaning, coherence, poetic quality, and fluency. Notably, the creation of good poetry entails considerations of ...

This article presents a comparative analysis of three distinct prompting techniques—simple zero-shot, few-shot, and role-based—for the task of summarizing articles from diverse domains, using two large language models (LLMs): GPT 3.5 and Llama 2. The ...

Automatic Text Summarization (ATS) is a research area that originated in the late 1950s and has gained increasing importance with the surging amount of text data available today. One of the key challenges in this area is how to quantitatively assess the ...

With the advent of the digital age, data privacy has become increasingly relevant, provoking widespread concern and attention. As technology facilitates increased communication and automation in various aspects of life, companies and organizations must ...

In Natural Language Processing (NLP), Parts of Speech (PoS) tagging is one of the most crucial steps of pre-processing in every language system. PoS tagging is the process of selecting the best suitable ‘part of speech category’ or ‘lexical class ...

Background and Context: Struggling with programming assignments while learning to program is a common phenomenon in programming courses around the world. Supporting struggling students is a common theme in Computing Education Research (CER), where a wide ...

The accurate evaluation of machine translation (MT) is a difficult task. Human evaluation (judgment) is considered to be the best, but it is time-consuming. Hence, the importance of developing an automatic evaluation metric got researchers’ ...

Deep generative models such as a family of GPT have exhibited super-human performance in natural language generation. However, the evaluation of the generated lacks the automated solutions and mostly requires human involved manual experiments. ...

Recent years have brought a surge of work on predicting pieces of source code, e.g., for code completion, code migration, program repair, or translating natural language into code. All this work faces the challenge of evaluating the quality of a ...

Commit messages play an important role in several software engineering tasks such as program comprehension and understanding program evolution. However, programmers neglect to write good commit messages. Hence, several Commit Message Generation (CMG) ...

Signboard detection and recognition is an important task in automated context-aware marketing. Recently many scripting languages like Latin, Japanese, and Chinese have been effectively detected by several machine learning algorithms. As compared ...

Machine translation is one of the pioneer applications of natural language processing and artificial intelligence. Automatic evaluation of the translation performance of the machine translators is one of the most challenging tasks, as manual evaluation of ...

Farmers play a vital role in the Indian society. Their queries and doubts are important to be cleared as they affect the crops and thus the economy. With the boom in information sharing in the age of Internet, there are several agricultural ...

In this paper, we describe the development of an English-Amharic parallel corpus and Machine Translation (MT) experiments conducted on it. Two different tests have been achieved. Statistical Machine Translation (SMT) and Neural Machine Translation ...

Machine Translation is an effort to bridge language barriers and misinterpretations, making communication more convenient through the automatic translation of languages. The quality of translations produced by corpus-based approaches predominantly depends ...

Although Lexical ambiguity, i.e., the presence of two or more meanings for a single word, is an inherent and challenging problem for machine translation systems. Even though the use of recurrent neural networks (RNN) and attention mechanisms are ...

Image captioning is a growing field of research that has taken hold of the research community. It is a challenging task owing to the complexity of natural language generation and the difficulty involved in feature extraction from a diverse ...

The present work aims at analyzing the social media data for code-switching and transliterated to English language using the special kind of recurrent neural network (RNN) called Long Short-Term Memory (LSTM) Network. During the course of work, ...

Automatic caption generation from images is an interesting and mainstream direction in the field of machine learning. This method enables us to build a powerful computer model that can interpret the implicit semantic information of images. However,...

• A carrier-less text steganography based on CNN-LSTM network is proposed.
• SSH scheme based on beam search can be applied in model sharing situation.
• HH scheme for model-free extraction with hash function is proposed.
• The ...

It is a challenge to conduct natural language steganography on Online interactive platforms such as photo-sharing websites since the stego texts should be consistent with the content of the images. In this paper, a novel natural language ...