Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

5-2024

Abstract

Web applications serve as vital interfaces for users to access information, perform various tasks, and engage with content. Traditional web designs have predominantly focused on user interfaces and static experiences. With the advent of large language models (LLMs), there’s a paradigm shift as we integrate LLM-powered agents into these platforms. These agents bring forth crucial human capabilities like memory and planning to make them behave like humans in completing various tasks, effectively enhancing user engagement and offering tailored interactions in web applications. In this tutorial, we delve into the cutting-edge techniques of LLM-powered agents across various web applications, such as web mining, social networks, recommender systems, and conversational systems. We will also explore the prevailing challenges in seamlessly incorporating these agents and hint at prospective research avenues that can revolutionize the way we interact with web platforms.

Keywords

Large Language Model, Social Network, Recommendation, Conversational Agent

Discipline

Databases and Information Systems | Programming Languages and Compilers

Research Areas

Data Science and Engineering

Areas of Excellence

Digital transformation

Publication

WWW '24: Companion Proceedings of the ACM on Web Conference 2024, Singapore, May 13-17

First Page

1242

Last Page

1245

ISBN

9798400701726

Identifier

10.1145/3589335.3641240

Publisher

ACM

City or Country

New York

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1145/3589335.3641240

Download

Share

COinS