Torrent details for "White R. Information Access in the Era of Generative AI 2024" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
None
Total Size:
9.6 MB
Info Hash:
F86295000B260D7C5324B6B93D3305F685504881
Added By:
Added:
April 22, 2026, 2:43 a.m.
Stats:
|
(Last updated: April 22, 2026, 2:46 a.m.)
| File | Size |
|---|---|
| White R. Information Access in the Era of Generative AI 2024.pdf | 9.6 MB |
Name
DL
Uploader
Size
S/L
Added
NOTE
SOURCE: White R. Information Access in the Era of Generative AI 2024
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
Textbook in PDF format Discusses GenAI and its many dimensions in information access and interaction. Covers GenAI/GenIR foundations, interactions, evaluations, sociotechnical implications and recommendations. Targeted at researchers and graduate students in information retrieval or GenAI applications. Generative Artificial Intelligence (GenAI) has emerged as a groundbreaking technology that promises to revolutionize many industries as well as people’s personal and professional lives. This book discusses GenAI and its role in information access - often referred to as Generative Information Retrieval (GenIR) - or more broadly, information interaction. The role of GenAI in information access is complex and dynamic, with many dimensions. To address this, following a brief introduction to GenAI and GenIR, the remainder of the book provides eight chapters, each targeting a different dimension or sub-topic. These cover foundations of GenIR, interactions with GenIR systems, adapting them to users, tasks, and scenarios, improving them based on user feedback, GenIR evaluation, the sociotechnical implications of GenAI for information access, recommendations within GenIR, and the future of information access with GenIR. The book is targeted at graduate students and researchers interested in issues of information retrieval, access, and interactions, as well as applications of GenAI in various informational contexts. While some of the parts assume prior background in IR or AI, most others do not, making this book suitable for adoption in various classes as a primary source or as a supplementary material
×