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Related papers: Toward an AI-Native Internet: Rethinking the Web A…

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New systems employ Machine Learning to sift through large knowledge sources, creating flexible Large Language Models. These models discern context and predict sequential information in various communication forms. Generative AI, leveraging…

Artificial Intelligence · Computer Science 2023-07-19 Ted Selker

Background: The rapid advancement of large language models (LLMs) has given rise to AI-native applications, a new paradigm in software engineering that fundamentally redefines how software is designed, developed, and evolved. Despite their…

Software Engineering · Computer Science 2025-09-17 Lingli Cao , Shanshan Li , Ying Fan , Danyang Li , Chenxing Zhong

The increasing complexity and scale of modern telecommunications networks demand intelligent automation to enhance efficiency, adaptability, and resilience. Agentic AI has emerged as a key paradigm for intelligent communications and…

Networking and Internet Architecture · Computer Science 2025-02-25 Ruichen Zhang , Shunpu Tang , Yinqiu Liu , Dusit Niyato , Zehui Xiong , Sumei Sun , Shiwen Mao , Zhu Han

The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The amount of information grows billions of databases. We need to search the information will specialize tools known…

Artificial Intelligence · Computer Science 2011-02-07 G. Madhu , Dr. A. Govardhan , Dr. T. V. Rajinikanth

Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are revolutionizing network management systems, paving the way towards fully autonomous and self-optimizing communication systems. These models enable networks to…

Networking and Internet Architecture · Computer Science 2026-01-07 Faisal Zaman , Ouns Bouachir , Moayad Aloqaily , Ismaeel Al Ridhawi

Large language models (LLMs) have triggered tremendous success to empower our daily life by generative information. The personalization of LLMs could further contribute to their applications due to better alignment with human intents.…

Machine Learning · Computer Science 2024-03-12 Yuxuan Chen , Rongpeng Li , Zhifeng Zhao , Chenghui Peng , Jianjun Wu , Ekram Hossain , Honggang Zhang

The rapid advancement of large language models (LLMs) has made detecting AI-generated text an increasingly critical challenge. Traditional methods often fail to capture the nuanced semantic differences between human and machine-generated…

Computation and Language · Computer Science 2025-02-03 Lifu Gao , Ziwei Liu , Qi Zhang

Information retrieval is a cornerstone of modern knowledge acquisition, enabling billions of queries each day across diverse domains. However, traditional keyword-based search engines are increasingly inadequate for handling complex,…

Retrieving and extracting knowledge from extensive research documents and large databases presents significant challenges for researchers, students, and professionals in today's information-rich era. Existing retrieval systems, which rely…

Information Retrieval · Computer Science 2025-02-06 Mohammed-Khalil Ghali , Abdelrahman Farrag , Daehan Won , Yu Jin

As more content generated by large language models (LLMs) floods into the Internet, information retrieval (IR) systems now face the challenge of distinguishing and handling a blend of human-authored and machine-generated texts. Recent…

Information Retrieval · Computer Science 2025-08-26 Wei Huang , Keping Bi , Yinqiong Cai , Wei Chen , Jiafeng Guo , Xueqi Cheng

The rapid adoption of generative AI-powered search engines like ChatGPT, Perplexity, and Gemini is fundamentally reshaping information retrieval, moving from traditional ranked lists to synthesized, citation-backed answers. This shift…

Information Retrieval · Computer Science 2025-09-15 Mahe Chen , Xiaoxuan Wang , Kaiwen Chen , Nick Koudas

The emergence of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) has marked a new era of Natural Language Processing (NLP), introducing unprecedented capabilities that are revolutionizing various domains. This paper…

Computation and Language · Computer Science 2024-08-26 Desta Haileselassie Hagos , Rick Battle , Danda B. Rawat

Large Language Models (LLMs) have revolutionized the domain of natural language processing (NLP) with remarkable capabilities of generating human-like text responses. However, despite these advancements, several works in the existing…

Computation and Language · Computer Science 2023-10-25 Soumya Suvra Ghosal , Souradip Chakraborty , Jonas Geiping , Furong Huang , Dinesh Manocha , Amrit Singh Bedi

This paper offers an insightful examination of how currently top-trending AI technologies, i.e., generative artificial intelligence (Generative AI) and large language models (LLMs), are reshaping the field of video technology, including…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Pengyuan Zhou , Lin Wang , Zhi Liu , Yanbin Hao , Pan Hui , Sasu Tarkoma , Jussi Kangasharju

Information technology has profoundly altered the way humans interact with information. The vast amount of content created, shared, and disseminated online has made it increasingly difficult to access relevant information. Over the past two…

Information Retrieval · Computer Science 2025-04-14 Yu Zhang , Shutong Qiao , Jiaqi Zhang , Tzu-Heng Lin , Chen Gao , Yong Li

Large Language Models (LLMs) are a class of generative AI models built using the Transformer network, capable of leveraging vast datasets to identify, summarize, translate, predict, and generate language. LLMs promise to revolutionize…

Information Retrieval · Computer Science 2024-03-05 Chunhe Ni , Jiang Wu , Hongbo Wang , Wenran Lu , Chenwei Zhang

One goal of AI (and AGI) is to identify and understand specific mechanisms and representations sufficient for general intelligence. Often, this work manifests in research focused on architectures and many cognitive architectures have been…

Artificial Intelligence · Computer Science 2025-06-17 Robert E. Wray , James R. Kirk , John E. Laird

Generative AI plays an increasing role during software engineering activities to make them, e.g., more efficient or provide better quality. However, it is often unclear how much benefit LLMs really provide. We concentrate on software…

Software Engineering · Computer Science 2026-01-28 Frank Elberzhager , Matthias Gerbershagen , Joshua Ginkel

This study presents a novel framework for smart search in digital archival systems, leveraging the capabilities of Large Language Models (LLMs) to enhance information retrieval. By employing a Retrieval-Augmented Generation (RAG) approach,…

Artificial Intelligence · Computer Science 2025-01-14 Ha Dung Nguyen , Thi-Hoang Anh Nguyen , Thanh Binh Nguyen

Since its emergence in the 1990s the World Wide Web (WWW) has rapidly evolved into a huge mine of global information and it is growing in size everyday. The presence of huge amount of resources on the Web thus poses a serious problem of…

Information Retrieval · Computer Science 2011-02-04 Debajyoti Mukhopadhyay , Aritra Banik , Sreemoyee Mukherjee , Jhilik Bhattacharya , Young-Chon Kim