KDD Workshop on Evaluation and Trustworthiness of Agentic and Generative AI
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.
Authors
- Chandan K. Reddy (ORCID: https://orcid.org/0000-0003-2839-3662)
- Yarong Feng (ORCID: https://orcid.org/0000-0001-7595-6945)
- Shujing Dong (ORCID: https://orcid.org/0009-0008-0240-681X)
- George Karypis (ORCID: https://orcid.org/0000-0003-2753-1437)
- Zheng Chen (ORCID: https://orcid.org/0000-0003-4406-2193)
- Yuan Ling (ORCID: https://orcid.org/0000-0002-1135-5240)
- Sadid A. Hasan (ORCID: https://orcid.org/0000-0002-5665-7752)
Institutions
- Microsoft (United States) (US)
- University of Minnesota (US)
- Amazon (United States) (US)
- Bellevue Hospital Center (US)
- Virginia Tech (US)
Publication Details
- Published
- 2025-08-03
- DOI
- https://doi.org/10.1145/3711896.3737854
- Primary Topic
- Explainable Artificial Intelligence (XAI)
- Type
- article
- Field-Weighted Citation Impact
- 0.00