We are excited to announce a call for contributed talks and posters/demos at the upcoming Stanford Graph Learning Workshop.

We are inviting two types of contributions (you can sign up for one or both):

Short talks: Give a 10-20 minute presentation on the main stage. Posters/demos: Present your poster/demo at a poster session. We expect the contributions of two types:

Significant Methodological Advancements, Open Source Tools, and Benchmarks: We are inviting contributions on the latest advancements in agentic systems, relational deep learning and AI, fast LLM inference, as well as contributions in the areas of open source tools and benchmarks that enable the community to evaluate and compare the performance of different methods and models. Discussions about reproducibility, fairness, robustness, scalability, and efficiency are also encouraged.

Applications and Industrial Deployments: We are inviting contributions that highlight the use and impact of agents and relational deep learning to real-world applications and real-world databases, focusing on the challenges faced during deployment, strategies adopted to overcome these challenges, and the ultimate impact achieved. Share your experiences, learnings, and insights to help the community understand implications and benefits of agentic systems and graph-based AI.

To submit your proposal, please fill out the application form below by Oct 1st. Selected contributors will then be notified and will be invited to present in-person at the workshop. We look forward to receiving your contributions to this exciting workshop!