1 citations · 1 across the 3 of their papers we have counts for
6 papers
Workflow Cards: Structured Summaries of Workflow Executions Using Provenance Data
Nicola Giuseppe Marchioro, Gabriele Padovani, Amal Gueroudji +5
Model Cards and Data Cards have demonstrated the value of structured, human-readable documentation for machine learning artifacts, capturing their context, parameters, limitations,…
Automated Data Readiness for Scientific AI
Sean R. Wilkinson, Valentine G. Anantharaj, Jong Youl Choi +8
Leadership computing facilities steward large-scale scientific datasets that routinely require substantial transformation before serving as AI training data. However, no existing f…
An Agentic AI Framework to Accelerate Scientific Discovery in Plant Phenotyping
Renan Souza, Daniel Rosendo, Kelsey Carter +6
High-throughput plant phenotyping now generates image derived datasets far faster than scientists can analyze them. At Oak Ridge National Laboratory's Advanced Plant Phenotyping La…
LLM Agents for Interactive Workflow Provenance: Reference Architecture and Evaluation Methodology
Renan Souza, Timothy Poteet, Brian Etz +5
Modern scientific discovery increasingly relies on workflows that process data across the Edge, Cloud, and High Performance Computing (HPC) continuum. Comprehensive and in-depth an…
The (R)evolution of Scientific Workflows in the Agentic AI Era: Towards Autonomous Science
Woong Shin, Renan Souza, Daniel Rosendo +4
Modern scientific discovery increasingly requires coordinating distributed facilities and heterogeneous resources, forcing researchers to act as manual workflow coordinators rather…
PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflows
Renan Souza, Amal Gueroudji, Stephen DeWitt +5
Large Language Models (LLMs) and other foundation models are increasingly used as the core of AI agents. In agentic workflows, these agents plan tasks, interact with humans and pee…