Web Science and Digital Libraries Research Group

Image Generated by DALL-E The utility of Large Language Models (LLMs) across diverse tasks raises important questions about the role of AI in web archive contexts, particularly in facilitating change analysis tasks. For instance, can LLMs effectively detect and analyze changes in webpages? How can this be achieved? What advantages and limitations do AI approaches have compared to traditional methods?.  In this blog post, I summarize our paper  “Exploring Large Language Models for Analyzing Changes in Web Archive Content: A Retrieval-Augmented Generation Approach”  ( Jhon G. Botello ,  Lesley Frew ,  Jose J. Padilla ,  Michele C. Weigle ) published at the  9th Computational Archival Science (CAS) Workshop 2024  (check Lesley Frew's trip report for more details about the workshop). The paper represents our first step in determining the ability of LLMs and the extent to which they can assist with change analysis tasks. Motivation As we interact...

CIKM 2024 took place in Boise, Idaho, in the Mountain West part of the United States. The mountains in the background distinguish the pictured Idaho State Capitol from the US Capitol. ACM CIKM 2024 was held from October 21 through 25 in Boise, Idaho. There were over 800 attendees, including over 400 students! Parallel topic sessions included presentations for full papers, resource papers, and invited journal papers. Short papers were presented as posters altogether in one session. The three attendees writing this trip report are Himarsha Jayanetti and Lesley Frew (WS-DL PhD students at ODU) and Gangani Ariyarathne (PhD student at William & Mary supervised by WS-DL alum Alexander Nwala). Monday Tutorials Day 1 at #CIKM2024 ! Attending the tutorial "Collecting and Analyzing Public Data from Mastodon" by @harisbinzia to learn and gain hands-on experience with the decentralized social network, Mastodon. @WebSciDL pic.twitter.com/0GA4aC1PZ4 — Himarsha R. Jayanetti (@Himarsh...