Skip to main navigation Skip to search Skip to main content

KDD Workshop on Evaluation and Trustworthiness of Agentic and Generative AI

  • Yuan Ling
  • , Shujing Dong
  • , Zheng Chen
  • , Yarong Feng
  • , Sadid Hasan
  • , George Karypis
  • , Chandan K. Reddy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The rapid deployment of Generative and Agentic AI systems-ranging from large language models to autonomous agents-has created a critical need for rigorous and trustworthy evaluation methodologies. As these models influence real-world decision-making, traditional performance metrics alone fall short in capturing issues of safety, ethical alignment, misinformation, and human-centered usability. This workshop addresses these challenges by fostering interdisciplinary discussions and innovations in evaluation strategies that go beyond conventional benchmarks. Topics include holistic and multi-perspective assessments, scalable evaluation pipelines, reasoning and goal alignment in agentic behavior, misinformation detection, cross-modal generation, and trust calibration. By advancing robust, user-centric, and societally grounded evaluation practices, this workshop contributes to expanding KDD's methodological frontier into the emerging domain of responsible AI systems.

Original languageEnglish (US)
Title of host publicationKDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery
Pages6286-6287
Number of pages2
ISBN (Electronic)9798400714542
DOIs
StatePublished - Aug 3 2025
Externally publishedYes
Event31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025 - Toronto, Canada
Duration: Aug 3 2025Aug 7 2025

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Volume2
ISSN (Print)2154-817X

Conference

Conference31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025
Country/TerritoryCanada
CityToronto
Period8/3/258/7/25

Bibliographical note

Publisher Copyright:
© 2025 Owner/Author.

Keywords

  • bias and fairness
  • cross-modal evaluation
  • ethical considerations in ai
  • evaluation metrics
  • generative ai models
  • trustworthiness

Fingerprint

Dive into the research topics of 'KDD Workshop on Evaluation and Trustworthiness of Agentic and Generative AI'. Together they form a unique fingerprint.

Cite this